1. Medición de una variable:
    Se hace uso de un instrumento de medicíon para obtener un valor preciso con un margen de error que es marcado por el mismo instrumento.

Estimación de una variable:
Según lo que previamente conoce el investigador se toma una medida que puede ser similar a la tomada con el instrumento.

  1. Ecuación:

\(Altura^2 = Vmas^2- Vmenos^2\)

Siempre y cuando las vistas menos estén en negativo.

  1. Alometría:
    Crecimiento de una parte de un organismo en relación al crecimiento del organismo completo o una parte de este; ii) el estudio de las consecuencias del tamaño sobre las formas y procesos orgánicos (Niklas 1994).

Considerando que las parcelas miden 0.04 ha y que son cuatro bosques

  1. Realizar histogramas que muestren la distribución diamétrica de cada tipo de bosque, empleando intervalos de clase de 10 cm cada uno.
# Cargando librerias 
library(tidyverse)
library(ggpubr)
library(dplyr)

# Leyendo base de datos

datos <- read.csv2("Datos_taller1.csv")

Se calcula el DAP

datos <- datos %>% 
  mutate(DAP_cm=CAP_cm/pi)

Histogramas por bosque

# Bosque 1
bosque1 <- datos %>% 
  subset(datos$Bosque == "A")


# Bosque 2
bosque2 <- datos %>% 
  subset(datos$Bosque == "B")

# Bosque 3
bosque3 <- datos %>% 
  subset(datos$Bosque == "C")

# Bosque 4
bosque4 <- datos %>% 
  subset(datos$Bosque == "D")
# Se saca el rango de los datos del DAP para cada bosque 

range(bosque1$DAP_cm)
## [1] 12.6369 39.8524
range(bosque2$DAP_cm)
## [1] 10.00130 74.42085
range(bosque3$DAP_cm)
## [1] 12.35042 54.43099
range(bosque4$DAP_cm)
## [1] 10.00130 73.43409
# En la función `breaks()` va el valor mínimo, máximo y cada cuanto quiero el intervalo 

par(mfrow = c(2,2))
hist1 <- hist(bosque1$DAP_cm, breaks = seq(10,40,10))
hist2 <- hist(bosque2$DAP_cm, breaks = seq (10,80,10))
hist3 <- hist(bosque3$DAP_cm, breaks = seq(10,60,10))
hist4 <- hist(bosque4$DAP_cm, breaks = seq(10,80,10))

El pimer bosque tiene individuos de 10 a 40 cm, siendo los de 40 cm en muy poca cantidad por lo cúal es posible que es un bosque muy joven y probablemente una plantación por que todos los individuos están creciendo al mismo tiempo.
En cuanto al bosque 2 y 4 se pude observr que presenta mucha similitud en cuanto a la distribución de sus individuos, los cuales varían mucho en sus DAP, se podría suponer que son bosques con más edad, los cuales presentan más estratos. El bosque 3 también presenta esta variación pero con la diferencia que tiene individuos más pequeños y en menor cantidad, se puede suponer que es un bosque con menos edad que el 2 y 4.

  1. Número de individuos por (ha), diámetro cuadráticomedio (cm) área basal (\(m^2ha^-1\)) para cada parcela y elaborar una tabla síntesis
# Se debe de sacar la relación primero para saber cuantas parcelas de 0,04 ha me caben en una parcela

1/0.04 # En una Ha caben 25 parcelas de 0,04 Ha cada una 
## [1] 25
# Creando la variable `plot` para que las parcelas se relacionen con cada tipo de bosque, el segundo argumento es como quiero que lo separe, para este caso es con "_"

datos$plot <- paste0(datos$Bosque, "_", datos$Parcela)
# Individuos por parcela

ind_parcela <- table(datos$Parcela)
ind_parcela
## 
##  P_1 P_10 P_11 P_12  P_2  P_3  P_4  P_5  P_6  P_7  P_8  P_9 
##  125   84  105  104  104  110  101   97  110  105   84  112
# Primero se deben de sacar los individuos por parcela para despues saber cuantos hay por Ha
ind_Ha <- ind_parcela*25
ind_Ha
## 
##  P_1 P_10 P_11 P_12  P_2  P_3  P_4  P_5  P_6  P_7  P_8  P_9 
## 3125 2100 2625 2600 2600 2750 2525 2425 2750 2625 2100 2800
# Individuos por Ha por bosque

ind_Ha_bosq <- as.vector(table(datos$plot)*25)
ind_Ha_bosq
##  [1]  675  575  500  500  625  625  575  700  650  625  450  675  925  525
## [15]  675  550  775  825  775  450  650  800  725  650  575  525  450  350
## [29]  400  575  500  550  625  425  375  625  950  475 1000 1200  800  725
## [43]  675  725  825  775  550  850
# Primero se debe hallar el área basal

datos <- datos %>% 
  mutate(AB_cm = (pi/4)*DAP_cm^2)

# Como el diámetro cuadrático medio se da en metros cuadrados,y el área basal se calculó en cm cuadrados, se debe hacer la conversión.

datos$AB_m <- datos$AB_cm/10000

# El área basal se debe de hallar por Ha 

AB_ha <- tapply(datos$AB_m,datos$plot, sum)*25 # el tapply aplica una operación (párametro 3) a cada celda (párametro 1)y las agrupa según el parametro que queramos (párametro 2)
AB_ha
##     A_P_1    A_P_10    A_P_11    A_P_12     A_P_2     A_P_3     A_P_4 
## 29.728592 26.754813 20.511636 20.796126 27.407635 28.067211 27.388328 
##     A_P_5     A_P_6     A_P_7     A_P_8     A_P_9     B_P_1    B_P_10 
## 28.882202 30.788526 30.398616 20.449341 26.898882 22.850305 35.605977 
##    B_P_11    B_P_12     B_P_2     B_P_3     B_P_4     B_P_5     B_P_6 
## 22.965457 29.735260 32.634759 35.218447 34.619111 21.367617 24.964340 
##     B_P_7     B_P_8     B_P_9     C_P_1    C_P_10    C_P_11    C_P_12 
## 34.885157 33.177871 32.814089 25.099530 19.159572 15.237403 11.518746 
##     C_P_2     C_P_3     C_P_4     C_P_5     C_P_6     C_P_7     C_P_8 
## 18.519664 20.099435 24.450107 30.164663 23.078095 20.808078 16.485006 
##     C_P_9     D_P_1    D_P_10    D_P_11    D_P_12     D_P_2     D_P_3 
## 34.799570 41.359433  8.031261 28.291876 28.713869 27.568512 37.955623 
##     D_P_4     D_P_5     D_P_6     D_P_7     D_P_8     D_P_9 
## 14.337702 19.754518 41.644999 24.853875 23.823555 19.951483
library(knitr)
# Se aplica la fórmula de el diámetro cuadrático medio 

dqm <- sqrt((40000/pi)*AB_ha/ind_Ha_bosq) 
dqm
##    A_P_1   A_P_10   A_P_11   A_P_12    A_P_2    A_P_3    A_P_4    A_P_5 
## 23.68047 24.34009 22.85442 23.01237 23.62930 23.91193 24.62657 22.92035 
##    A_P_6    A_P_7    A_P_8    A_P_9    B_P_1   B_P_10   B_P_11   B_P_12 
## 24.55799 24.88525 24.05406 22.52528 17.73496 29.38576 20.81329 26.23672 
##    B_P_2    B_P_3    B_P_4    B_P_5    B_P_6    B_P_7    B_P_8    B_P_9 
## 23.15498 23.31381 23.84856 24.58821 22.11355 23.56299 24.13850 25.35295 
##    C_P_1   C_P_10   C_P_11   C_P_12    C_P_2    C_P_3    C_P_4    C_P_5 
## 23.57512 21.55601 20.76368 20.47027 24.27960 21.09663 24.95229 26.42548 
##    C_P_6    C_P_7    C_P_8    C_P_9    D_P_1   D_P_10   D_P_11   D_P_12 
## 21.68278 24.96759 23.65832 26.62576 23.54402 14.67236 18.97955 17.45462 
##    D_P_2    D_P_3    D_P_4    D_P_5    D_P_6    D_P_7    D_P_8    D_P_9 
## 20.94675 25.81809 16.44534 18.62599 25.35184 20.20697 23.48427 17.28754
resultados <- data.frame(ind_Ha_bosq, AB_ha, dqm) %>% 
  kable()
resultados
ind_Ha_bosq AB_ha dqm
A_P_1 675 29.728592 23.68047
A_P_10 575 26.754813 24.34009
A_P_11 500 20.511636 22.85442
A_P_12 500 20.796126 23.01237
A_P_2 625 27.407635 23.62930
A_P_3 625 28.067211 23.91193
A_P_4 575 27.388328 24.62657
A_P_5 700 28.882202 22.92035
A_P_6 650 30.788526 24.55799
A_P_7 625 30.398616 24.88525
A_P_8 450 20.449341 24.05406
A_P_9 675 26.898882 22.52528
B_P_1 925 22.850305 17.73496
B_P_10 525 35.605977 29.38576
B_P_11 675 22.965457 20.81329
B_P_12 550 29.735260 26.23672
B_P_2 775 32.634759 23.15498
B_P_3 825 35.218447 23.31381
B_P_4 775 34.619111 23.84856
B_P_5 450 21.367617 24.58821
B_P_6 650 24.964340 22.11355
B_P_7 800 34.885157 23.56299
B_P_8 725 33.177871 24.13850
B_P_9 650 32.814089 25.35295
C_P_1 575 25.099530 23.57512
C_P_10 525 19.159572 21.55601
C_P_11 450 15.237403 20.76368
C_P_12 350 11.518746 20.47027
C_P_2 400 18.519664 24.27960
C_P_3 575 20.099435 21.09663
C_P_4 500 24.450107 24.95229
C_P_5 550 30.164663 26.42548
C_P_6 625 23.078095 21.68278
C_P_7 425 20.808078 24.96759
C_P_8 375 16.485006 23.65832
C_P_9 625 34.799570 26.62576
D_P_1 950 41.359433 23.54402
D_P_10 475 8.031261 14.67236
D_P_11 1000 28.291876 18.97955
D_P_12 1200 28.713869 17.45462
D_P_2 800 27.568512 20.94675
D_P_3 725 37.955623 25.81809
D_P_4 675 14.337702 16.44534
D_P_5 725 19.754518 18.62599
D_P_6 825 41.644999 25.35184
D_P_7 775 24.853875 20.20697
D_P_8 550 23.823555 23.48427
D_P_9 850 19.951483 17.28754
ind_bos_mean <- apply(table(datos$Bosque, datos$Parcela), 1, mean)*25
ind_bos_mean
##        A        B        C        D 
## 597.9167 693.7500 497.9167 795.8333
ind_bos_sd <- apply(table(datos$Bosque, datos$Parcela), 1, sd)*25
ind_bos_sd
##         A         B         C         D 
##  79.38566 137.80957  96.21138 195.64385
AB_bosq_mean <- apply(tapply(datos$AB_m, list(datos$Bosque, datos$Parcela), sum), 1, mean)*25
AB_bosq_mean
##        A        B        C        D 
## 26.50599 30.06987 21.61832 26.35723
AB_bosq_sd <- apply(tapply(datos$AB_m, list(datos$Bosque, datos$Parcela), sum), 1, sd)*25
AB_bosq_sd
##         A         B         C         D 
##  3.801760  5.471500  6.443694 10.347102
#ANOVA para comparar tipos de bosque
anova <- table(datos$Bosque, datos$Parcela)
anova
##    
##     P_1 P_10 P_11 P_12 P_2 P_3 P_4 P_5 P_6 P_7 P_8 P_9
##   A  27   23   20   20  25  25  23  28  26  25  18  27
##   B  37   21   27   22  31  33  31  18  26  32  29  26
##   C  23   21   18   14  16  23  20  22  25  17  15  25
##   D  38   19   40   48  32  29  27  29  33  31  22  34
# se realizan dos vectores para correr el anova

valor <- c(anova[1,], anova[2,], anova[3,],anova[4,] )
agrupacion <- c(rep("A", 12), rep("B",12), rep("C",12), rep("D",12))
a <- aov(valor~agrupacion)
a
## Call:
##    aov(formula = valor ~ agrupacion)
## 
## Terms:
##                 agrupacion Residuals
## Sum of Squares    940.2292 1281.7500
## Deg. of Freedom          3        44
## 
## Residual standard error: 5.397285
## Estimated effects may be unbalanced
summary(a)
##             Df Sum Sq Mean Sq F value Pr(>F)    
## agrupacion   3  940.2  313.41   10.76  2e-05 ***
## Residuals   44 1281.8   29.13                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(a)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = valor ~ agrupacion)
## 
## $agrupacion
##          diff        lwr       upr     p adj
## B-A  3.833333  -2.049843  9.716510 0.3159589
## C-A -4.000000  -9.883177  1.883177 0.2799444
## D-A  7.916667   2.033490 13.799843 0.0044015
## C-B -7.833333 -13.716510 -1.950157 0.0049051
## D-B  4.083333  -1.799843  9.966510 0.2629525
## D-C 11.916667   6.033490 17.799843 0.0000144
boxplot(valor~agrupacion)

anova <- tapply(datos$AB_m,list(datos$Bosque, datos$Parcela),sum)
anova
##         P_1      P_10      P_11      P_12       P_2       P_3       P_4
## A 1.1891437 1.0701925 0.8204655 0.8318450 1.0963054 1.1226884 1.0955331
## B 0.9140122 1.4242391 0.9186183 1.1894104 1.3053904 1.4087379 1.3847644
## C 1.0039812 0.7663829 0.6094961 0.4607498 0.7407865 0.8039774 0.9780043
## D 1.6543773 0.3212504 1.1316750 1.1485548 1.1027405 1.5182249 0.5735081
##         P_5       P_6       P_7       P_8       P_9
## A 1.1552881 1.2315410 1.2159446 0.8179736 1.0759553
## B 0.8547047 0.9985736 1.3954063 1.3271148 1.3125635
## C 1.2065865 0.9231238 0.8323231 0.6594003 1.3919828
## D 0.7901807 1.6658000 0.9941550 0.9529422 0.7980593
# se realizan dos vectores para correr el anova

valor <- c(anova[1,], anova[2,], anova[3,],anova[4,] )
agrupacion <- c(rep("A", 12), rep("B",12), rep("C",12), rep("D",12))
a <- aov(valor~agrupacion)
summary(a)
##             Df Sum Sq Mean Sq F value Pr(>F)  
## agrupacion   3  0.693 0.23085   2.991  0.041 *
## Residuals   44  3.396 0.07719                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
TukeyHSD(a)
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = valor ~ agrupacion)
## 
## $agrupacion
##            diff        lwr         upr     p adj
## B-A  0.14255494 -0.1602873  0.44539715 0.5947395
## C-A -0.19550680 -0.4983490  0.10733541 0.3239283
## D-A -0.00595067 -0.3087929  0.29689154 0.9999473
## C-B -0.33806174 -0.6409039 -0.03521953 0.0233147
## D-B -0.14850561 -0.4513478  0.15433660 0.5620580
## D-C  0.18955613 -0.1132861  0.49239833 0.3508137
boxplot(valor~agrupacion)

La prueba demuestra que existe diferencias estadísticamente significativas entre los bosques.Esto se puede concluir, porque según la literatura, los valores p menores de 0,05 en la prueba ANOVA indican significancia, en este test se obtuvo un resultado de 0,041.

Suponiendo que las alturas de los individuos del bosque no se conocen, se pasa a mirar el DAP, ya que este está relacionado con las alturas. Uno de los criterios para escoger parcelas para realizar mediciones de altura es que estas tengan un amplio rango en los DAP ya que esto me permite realizar una gráfica adecuada para la representación de la relacion entre estas dos variables. Se procede a carcular el valor máximo y mínimo de DAP por cada parcel de cada bosque para así hallar un rango, luego las cinco mejores parcelas se organizan de mayor a menor, siendo la primera la de mayor rango

min_bosq_par <- tapply(datos$DAP_cm,list(datos$Bosque, datos$Parcela),min)
min_bosq_par
##        P_1     P_10     P_11     P_12      P_2      P_3      P_4      P_5
## A 12.95521 16.32930 15.34254 14.70592 16.36113 15.43803 16.87042 14.80141
## B 10.34507 10.12225 10.69521 10.31324 10.05859 10.02676 10.18592 10.00130
## C 12.70056 12.35042 13.75099 14.06930 13.30535 12.47775 15.59718 14.57859
## D 10.00130 10.18592 10.02676 10.12225 10.00130 10.59972 10.09042 10.15409
##        P_6      P_7      P_8      P_9
## A 14.41944 14.13296 14.13296 12.63690
## B 10.02676 10.00130 10.15409 10.18592
## C 13.75099 14.32394 14.38761 14.83324
## D 10.15409 10.31324 10.21775 10.12225
max_bosq_par <- tapply(datos$DAP_cm,list(datos$Bosque, datos$Parcela),max)
max_bosq_par
##        P_1     P_10     P_11     P_12      P_2      P_3      P_4      P_5
## A 30.08028 39.85240 37.14676 29.76197 37.11493 36.57381 33.93183 36.89212
## B 40.96648 74.42085 46.98254 57.80508 63.98029 58.12339 65.57184 49.33803
## C 47.74648 32.46761 35.01409 26.73803 42.65352 27.53381 34.21831 43.00367
## D 73.43409 22.12254 42.81268 35.55521 57.16846 70.53747 43.29014 64.93522
##        P_6      P_7      P_8      P_9
## A 30.20761 39.31127 28.96620 32.81775
## B 56.14986 46.25043 51.40705 72.09719
## C 33.23155 47.42817 36.60564 54.43099
## D 57.51860 64.80789 67.16339 53.79437
sort(max_bosq_par[1,]- min_bosq_par[1,], decreasing = TRUE)[1:5]
##      P_7     P_10      P_5     P_11      P_3 
## 25.17831 23.52310 22.09071 21.80423 21.13578
sort(max_bosq_par[2,]- min_bosq_par[2,], decreasing = TRUE)[1:5]
##     P_10      P_9      P_4      P_2      P_3 
## 64.29860 61.91127 55.38592 53.92169 48.09662
sort(max_bosq_par[3,]- min_bosq_par[3,], decreasing = TRUE)[1:5]
##      P_9      P_1      P_7      P_2      P_5 
## 39.59775 35.04592 33.10423 29.34817 28.42507
sort(max_bosq_par[4,]- min_bosq_par[4,], decreasing = TRUE)[1:5]
##      P_1      P_3      P_8      P_5      P_7 
## 63.43279 59.93775 56.94564 54.78113 54.49465

A continuación se muestra las parcelas elegidas según el criterio anterior

Bosque A P_7 P_10 P_5 P_11 P_3
25.17831 23.52310 22.09071 21.80423 21.13578
Bosque B P_10 P_9 P_4 P_2 P_3
64.29860 61.91127 55.38592 53.92169 48.09662
Bosque C P_9 P_1 P_7 P_2 P_5
39.59775 35.04592 33.10423 29.34817 28.42507
Bosque D P_1 P_3 P_8 P_5 P_7
63.43279 59.93775 56.94564 54.78113 54.49465

Modelos

Modelo lineal (Modelo 1)

mod1 <- lm(Ht~DAP_cm, datos)
summary(mod1)
## 
## Call:
## lm(formula = Ht ~ DAP_cm, data = datos)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.7873 -0.3332  0.1699  0.4914  0.5707 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 9.808989   0.042341   231.7   <2e-16 ***
## DAP_cm      0.465573   0.001866   249.5   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.6222 on 1239 degrees of freedom
## Multiple R-squared:  0.9805, Adjusted R-squared:  0.9805 
## F-statistic: 6.225e+04 on 1 and 1239 DF,  p-value: < 2.2e-16
{par(mfrow=c(2,2))
plot(mod1)}

  • Cálculo de ANOVA
anova(mod1)
## Analysis of Variance Table
## 
## Response: Ht
##             Df  Sum Sq Mean Sq F value    Pr(>F)    
## DAP_cm       1 24099.9 24099.9   62252 < 2.2e-16 ***
## Residuals 1239   479.7     0.4                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  • Residuales Vs Predichos
Residuales1 <- residuals(mod1)
predichos1 <- predict(mod1)
plot(Residuales1~predichos1)

ggplot(datos, aes(predichos1, Residuales1))+
   geom_point()+
   geom_smooth(method = "lm")

  • Verificación de la normalidad de los residuales
shapiro.test(Residuales1)
## 
##  Shapiro-Wilk normality test
## 
## data:  Residuales1
## W = 0.79301, p-value < 2.2e-16
  • Cálculo del error
# Error absoluto
Error1 <- abs(((predichos1-datos$Ht)/datos$Ht)*100)
Error1
##            1            2            3            4            5 
## 2.539357e+00 2.065793e+00 2.500776e+00 2.244201e+00 2.529567e+00 
##            6            7            8            9           10 
## 1.996401e+00 1.501614e+00 2.082458e+00 2.426733e+00 1.075139e+00 
##           11           12           13           14           15 
## 2.544402e+00 2.148060e+00 2.660929e+00 2.370921e+00 2.555750e+00 
##           16           17           18           19           20 
## 2.390449e+00 2.155243e+00 2.553909e+00 2.467058e+00 2.513079e+00 
##           21           22           23           24           25 
## 2.403299e+00 2.555750e+00 8.804327e-01 2.455131e+00 2.556687e+00 
##           26           27           28           29           30 
## 2.521602e+00 2.500884e+00 2.019650e+00 2.401747e+00 2.518941e+00 
##           31           32           33           34           35 
## 2.547365e+00 4.781126e-01 2.495248e+00 2.474891e+00 2.528186e+00 
##           36           37           38           39           40 
## 2.245761e+00 1.902199e+00 2.534526e+00 2.199945e+00 2.266164e+00 
##           41           42           43           44           45 
## 1.075349e+00 2.515510e+00 2.536345e+00 2.388713e+00 1.656251e+00 
##           46           47           48           49           50 
## 2.135548e+00 2.544402e+00 1.579051e+00 2.521602e+00 2.561304e+00 
##           51           52           53           54           55 
## 5.554846e-01 1.630038e+00 2.556687e+00 1.738722e+00 2.224503e+00 
##           56           57           58           59           60 
## 1.973032e+00 2.324759e+00 2.545515e+00 2.065793e+00 2.508116e+00 
##           61           62           63           64           65 
## 2.468341e+00 2.543671e+00 2.041495e+00 2.551078e+00 2.543671e+00 
##           66           67           68           69           70 
## 2.497086e+00 2.541159e+00 2.152889e-01 2.201446e+00 2.442748e+00 
##           71           72           73           74           75 
## 9.643740e-01 2.365796e+00 2.524473e+00 2.064476e+00 7.149384e-01 
##           76           77           78           79           80 
## 1.020273e+00 2.490611e+00 1.360854e+00 2.378426e+00 2.533245e+00 
##           81           82           83           84           85 
## 2.541832e+00 7.674344e-01 2.518108e+00 2.406417e+00 2.526879e+00 
##           86           87           88           89           90 
## 2.551078e+00 1.705414e+00 2.526327e+00 2.497442e+00 2.460052e+00 
##           91           92           93           94           95 
## 2.551078e+00 2.201446e+00 2.552073e+00 1.553696e+00 2.563166e+00 
##           96           97           98           99          100 
## 2.468341e+00 2.385258e+00 2.549219e+00 2.386983e+00 2.535091e+00 
##          101          102          103          104          105 
## 2.440965e+00 2.539998e+00 2.513654e+00 2.548415e+00 1.579051e+00 
##          106          107          108          109          110 
## 2.176184e+00 2.524473e+00 7.108254e-01 2.439187e+00 2.383538e+00 
##          111          112          113          114          115 
## 1.344944e+00 2.488914e+00 2.242646e+00 2.317679e+00 2.364098e+00 
##          116          117          118          119          120 
## 2.519239e+00 2.535768e+00 2.383538e+00 2.520151e+00 2.176184e+00 
##          121          122          123          124          125 
## 6.445194e-01 7.244888e-01 6.530308e-01 2.492312e+00 2.329735e+00 
##          126          127          128          129          130 
## 2.264581e+00 1.047480e+00 2.156684e+00 2.518108e+00 2.531921e+00 
##          131          132          133          134          135 
## 2.326413e+00 2.520151e+00 2.080292e+00 1.900029e+00 2.222128e+00 
##          136          137          138          139          140 
## 2.297692e+00 2.542966e+00 2.448127e+00 1.680647e+00 2.455131e+00 
##          141          142          143          144          145 
## 2.532712e+00 2.544777e+00 2.148060e+00 2.493416e+00 2.284799e+00 
##          146          147          148          149          150 
## 2.555750e+00 2.081374e+00 2.560453e+00 1.053728e+00 2.538169e+00 
##          151          152          153          154          155 
## 2.539357e+00 2.149234e+00 2.513079e+00 7.888814e-01 2.557596e+00 
##          156          157          158          159          160 
## 7.108254e-01 1.973032e+00 2.523716e+00 2.375398e+00 2.329735e+00 
##          161          162          163          164          165 
## 2.519853e+00 1.604912e+00 2.544777e+00 2.526879e+00 2.223659e+00 
##          166          167          168          169          170 
## 1.657865e+00 1.902199e+00 2.527735e+00 2.548163e+00 4.000343e-02 
##          171          172          173          174          175 
## 2.427272e+00 2.222128e+00 1.804132e+00 2.530420e+00 2.537560e+00 
##          176          177          178          179          180 
## 1.353790e+00 2.527300e+00 2.538800e+00 8.038091e-01 2.266164e+00 
##          181          182          183          184          185 
## 2.320519e+00 2.555750e+00 2.344881e+00 2.495248e+00 2.110089e+00 
##          186          187          188          189          190 
## 1.353790e+00 2.551078e+00 2.152889e-01 2.245662e+00 2.542966e+00 
##          191          192          193          194          195 
## 2.530420e+00 8.244252e-01 2.488914e+00 2.521931e+00 2.537560e+00 
##          196          197          198          199          200 
## 2.329735e+00 2.272227e+00 1.576952e+00 2.715932e-01 6.824252e-01 
##          201          202          203          204          205 
## 2.531921e+00 2.548415e+00 2.557596e+00 2.528647e+00 2.064476e+00 
##          206          207          208          209          210 
## 2.451872e+00 2.177650e+00 2.504450e+00 2.523357e+00 1.186270e+00 
##          211          212          213          214          215 
## 1.995180e+00 1.184177e+00 2.513079e+00 2.511803e+00 2.246977e+00 
##          216          217          218          219          220 
## 9.370776e-01 2.515510e+00 2.329735e+00 2.044069e+00 1.047480e+00 
##          221          222          223          224          225 
## 2.498928e+00 3.036014e+00 2.309765e+00 2.548415e+00 2.546280e+00 
##          226          227          228          229          230 
## 2.376910e+00 2.044069e+00 9.643740e-01 2.492312e+00 1.853344e+00 
##          231          232          233          234          235 
## 1.878304e-01 2.506280e+00 2.533245e+00 2.390449e+00 2.517107e+00 
##          236          237          238          239          240 
## 2.537560e+00 2.220603e+00 1.679891e+00 2.531403e+00 2.156684e+00 
##          241          242          243          244          245 
## 1.246326e+00 2.530903e+00 4.490404e-01 2.543671e+00 1.923694e+00 
##          246          247          248          249          250 
## 2.544777e+00 2.467058e+00 2.490611e+00 2.421970e+00 2.555750e+00 
##          251          252          253          254          255 
## 1.424143e+00 2.484006e+00 1.755428e+00 2.437951e+00 5.740806e-01 
##          256          257          258          259          260 
## 2.465240e+00 6.815444e-01 6.098423e-02 2.565032e+00 2.486936e-01 
##          261          262          263          264          265 
## 2.565032e+00 2.548415e+00 1.102481e+00 2.546280e+00 1.102646e+00 
##          266          267          268          269          270 
## 2.520151e+00 1.238176e+00 8.804327e-01 2.283196e+00 2.531403e+00 
##          271          272          273          274          275 
## 2.470011e+00 7.956436e-01 2.394042e+00 2.110089e+00 2.538169e+00 
##          276          277          278          279          280 
## 2.509957e+00 1.450106e+00 2.199945e+00 2.511323e+00 1.755428e+00 
##          281          282          283          284          285 
## 2.446329e+00 2.482172e+00 7.602017e-01 2.128413e+00 2.497086e+00 
##          286          287          288          289          290 
## 2.375398e+00 2.520151e+00 3.106983e-01 2.500776e+00 2.998063e+00 
##          291          292          293          294          295 
## 6.361176e+00 6.988815e+00 6.719837e+00 5.250671e+00 1.219609e+00 
##          296          297          298          299          300 
## 1.397408e+00 6.845083e+00 7.108254e-01 2.421970e+00 2.230036e+00 
##          301          302          303          304          305 
## 3.218509e+00 4.936051e-01 2.122526e+00 1.884505e+00 2.497086e+00 
##          306          307          308          309          310 
## 5.083064e-01 2.465012e+00 5.958098e-01 4.395454e+00 3.729978e-01 
##          311          312          313          314          315 
## 1.153012e+00 3.489937e+00 2.477009e+00 5.753110e+00 1.947238e+00 
##          316          317          318          319          320 
## 1.528494e+00 1.344944e+00 2.715932e-01 3.334219e+00 2.544402e+00 
##          321          322          323          324          325 
## 6.098423e-02 6.219920e-02 1.460259e+00 9.104919e-02 3.179637e-02 
##          326          327          328          329          330 
## 1.657865e+00 1.770019e+00 2.199945e+00 2.796593e-01 3.756475e+00 
##          331          332          333          334          335 
## 2.388713e+00 6.604063e-01 1.969854e+00 4.718410e+00 2.104254e+00 
##          336          337          338          339          340 
## 1.906358e+00 9.267339e-02 1.119836e+00 5.579203e-02 2.482172e+00 
##          341          342          343          344          345 
## 2.385258e+00 3.529126e+00 1.576512e+00 5.207131e+00 1.597070e+00 
##          346          347          348          349          350 
## 1.947238e+00 7.667120e+00 1.852330e+00 8.305415e+00 3.529126e+00 
##          351          352          353          354          355 
## 6.940765e+00 7.956436e-01 1.426269e+00 1.253030e+00 1.909952e+00 
##          356          357          358          359          360 
## 2.518941e+00 7.108254e-01 5.047213e+00 5.947769e-01 2.633974e-01 
##          361          362          363          364          365 
## 2.367499e+00 4.322465e-01 2.798928e-01 2.500776e+00 1.053728e+00 
##          366          367          368          369          370 
## 2.527300e+00 2.544402e+00 5.966315e-01 6.892854e+00 5.648587e-01 
##          371          372          373          374          375 
## 4.071313e-01 1.246376e+00 7.717073e+00 2.474891e+00 3.106983e-01 
##          376          377          378          379          380 
## 6.221972e+00 1.219609e+00 7.924997e-01 6.988815e+00 1.450106e+00 
##          381          382          383          384          385 
## 3.836255e+00 2.879617e-02 2.552943e+00 2.071197e+00 1.475929e+00 
##          386          387          388          389          390 
## 2.735166e+00 3.716745e+00 2.370885e+00 2.153807e+00 1.808258e-01 
##          391          392          393          394          395 
## 5.740806e-01 5.753110e+00 1.475929e+00 1.265298e+00 6.259068e-01 
##          396          397          398          399          400 
## 7.602017e-01 2.329735e+00 4.592141e+00 8.804327e-01 3.923790e+00 
##          401          402          403          404          405 
## 5.015413e-01 1.153012e+00 7.674344e-01 7.389467e+00 2.809790e+00 
##          406          407          408          409          410 
## 5.015413e-01 2.178011e-01 2.123326e-01 4.961243e+00 7.163963e+00 
##          411          412          413          414          415 
## 1.735255e+00 2.194108e+00 2.155243e+00 8.872987e+00 2.423732e+00 
##          416          417          418          419          420 
## 2.283196e+00 1.020273e+00 6.530308e-01 4.355942e-01 4.953773e-01 
##          421          422          423          424          425 
## 4.347421e-01 4.355942e-01 1.994049e+00 2.735166e+00 7.789262e+00 
##          426          427          428          429          430 
## 3.177295e+00 1.426269e+00 2.302169e+00 1.211207e+00 2.922458e+00 
##          431          432          433          434          435 
## 2.660929e+00 5.456132e+00 6.604063e-01 2.559448e+00 6.361176e+00 
##          436          437          438          439          440 
## 4.000343e-02 7.391618e-01 3.411871e+00 3.106983e-01 1.980451e+00 
##          441          442          443          444          445 
## 1.460259e+00 4.385262e-01 1.631486e+00 5.958098e-01 2.448127e+00 
##          446          447          448          449          450 
## 1.019971e+00 2.477009e+00 5.520485e+00 3.608234e+00 1.324803e+00 
##          451          452          453          454          455 
## 5.648587e-01 6.314788e+00 6.988815e+00 1.973032e+00 1.604271e+00 
##          456          457          458          459          460 
## 7.717073e+00 1.902199e+00 1.884505e+00 3.026759e-01 4.699961e-01 
##          461          462          463          464          465 
## 4.503304e-01 2.557596e+00 1.424143e+00 7.789262e+00 1.170978e+00 
##          466          467          468          469          470 
## 2.294915e+00 1.497236e+00 2.223218e+00 4.148801e+00 1.926577e+00 
##          471          472          473          474          475 
## 5.753110e+00 1.705414e+00 4.490404e-01 2.403299e+00 3.411871e+00 
##          476          477          478          479          480 
## 1.700579e+00 6.815444e-01 6.625282e+00 1.578450e+00 4.312788e+00 
##          481          482          483          484          485 
## 2.370921e+00 1.501614e+00 5.798042e+00 1.970788e+00 4.170387e-01 
##          486          487          488          489          490 
## 1.902199e+00 2.437951e+00 1.047736e+00 1.265443e+00 2.157503e+00 
##          491          492          493          494          495 
## 2.152889e-01 1.808258e-01 2.152773e+00 3.084915e-02 9.551707e-01 
##          496          497          498          499          500 
## 7.888814e-01 9.392752e-02 3.887633e+00 8.898650e-01 5.958098e-01 
##          501          502          503          504          505 
## 2.796593e-01 1.825994e-01 7.438679e+00 2.222128e+00 2.846176e+00 
##          506          507          508          509          510 
## 6.824252e-01 2.525909e+00 8.898650e-01 1.320120e+00 1.129883e+00 
##          511          512          513          514          515 
## 1.516962e+00 1.754559e+00 2.421970e+00 2.491589e+00 8.809712e-01 
##          516          517          518          519          520 
## 6.988815e+00 4.676204e+00 2.122526e+00 1.886155e+00 5.204671e-01 
##          521          522          523          524          525 
## 5.004168e+00 2.129563e+00 4.042588e-01 5.015413e-01 1.020796e+00 
##          526          527          528          529          530 
## 5.500298e+00 6.098423e-02 3.716745e+00 1.704620e+00 4.849434e+00 
##          531          532          533          534          535 
## 6.098423e-02 7.389467e+00 1.770019e+00 2.158271e+00 1.124767e+01 
##          536          537          538          539          540 
## 1.494334e+00 5.331621e-01 3.614232e-01 2.321944e+00 1.804132e+00 
##          541          542          543          544          545 
## 4.271624e+00 2.453499e+00 3.320833e-01 2.697999e+00 4.676204e+00 
##          546          547          548          549          550 
## 8.248761e-01 1.665989e+00 8.804327e-01 2.708960e+00 2.326413e+00 
##          551          552          553          554          555 
## 1.020796e+00 1.423785e+00 2.385258e+00 3.663537e+00 1.379019e+00 
##          556          557          558          559          560 
## 1.206781e+01 2.459815e+00 2.875006e+00 3.036014e+00 1.324803e+00 
##          561          562          563          564          565 
## 6.815444e-01 1.928335e+00 1.053728e+00 7.488035e+00 2.497086e+00 
##          566          567          568          569          570 
## 2.483852e+00 2.550292e+00 7.888814e-01 1.324803e+00 1.527973e-01 
##          571          572          573          574          575 
## 1.392363e+00 1.358541e+00 2.518108e+00 1.909952e+00 1.878304e-01 
##          576          577          578          579          580 
## 1.735255e+00 2.477009e+00 1.874836e+00 8.248761e-01 5.500298e+00 
##          581          582          583          584          585 
## 2.268180e+00 2.513603e+00 1.291618e+00 6.314788e+00 2.400690e+00 
##          586          587          588          589          590 
## 2.560453e+00 2.044069e+00 1.528494e+00 2.419971e-01 2.122526e+00 
##          591          592          593          594          595 
## 2.369388e+00 4.676204e+00 2.218112e+00 2.623954e+00 2.219082e+00 
##          596          597          598          599          600 
## 1.320120e+00 4.312788e+00 3.450852e+00 2.440509e+00 1.730884e+00 
##          601          602          603          604          605 
## 5.798042e+00 1.022087e+00 1.102481e+00 2.998063e+00 1.778708e+00 
##          606          607          608          609          610 
## 2.482172e+00 6.100694e+00 8.573311e-01 5.589005e+00 7.115479e+00 
##          611          612          613          614          615 
## 5.207131e+00 9.125375e-01 3.074065e+00 3.074065e+00 6.672491e+00 
##          616          617          618          619          620 
## 3.177295e+00 1.597070e+00 2.158271e+00 1.042768e-01 4.071313e-01 
##          621          622          623          624          625 
## 2.090041e+00 5.947769e-01 2.385258e+00 2.458017e+00 2.960211e+00 
##          626          627          628          629          630 
## 1.397408e+00 2.654421e+00 2.509957e+00 2.549219e+00 7.963272e-01 
##          631          632          633          634          635 
## 2.174903e+00 2.364098e+00 4.042588e-01 2.347863e+00 1.845267e-01 
##          636          637          638          639          640 
## 2.302169e+00 2.542966e+00 2.365796e+00 2.531921e+00 2.442748e+00 
##          641          642          643          644          645 
## 3.011211e-01 1.438974e+00 2.248295e+00 2.194108e+00 3.011211e-01 
##          646          647          648          649          650 
## 1.808258e-01 1.012267e+00 2.269526e+00 1.902199e+00 1.371247e+00 
##          651          652          653          654          655 
## 2.328072e+00 2.488142e+00 1.264970e+00 2.440965e+00 2.546331e+00 
##          656          657          658          659          660 
## 1.878100e+00 1.341933e+00 2.370885e+00 2.326413e+00 1.680647e+00 
##          661          662          663          664          665 
## 2.480344e+00 2.423565e+00 2.177650e+00 1.778938e+00 1.654313e+00 
##          666          667          668          669          670 
## 7.956436e-01 1.923694e+00 2.548163e+00 2.245761e+00 2.484006e+00 
##          671          672          673          674          675 
## 2.529099e+00 1.186270e+00 2.364098e+00 2.533981e+00 2.437951e+00 
##          676          677          678          679          680 
## 2.556687e+00 3.295547e+00 2.555750e+00 4.699961e-01 1.494334e+00 
##          681          682          683          684          685 
## 2.242646e+00 6.815444e-01 2.400198e+00 2.321944e+00 2.531403e+00 
##          686          687          688          689          690 
## 1.397408e+00 1.265443e+00 2.148060e+00 2.067114e+00 2.431516e+00 
##          691          692          693          694          695 
## 2.326413e+00 2.489768e+00 2.516367e+00 1.020273e+00 1.019971e+00 
##          696          697          698          699          700 
## 1.799736e+00 2.111469e+00 6.219920e-02 1.799736e+00 2.493416e+00 
##          701          702          703          704          705 
## 2.563166e+00 2.527735e+00 2.156684e+00 2.347806e+00 1.656788e+00 
##          706          707          708          709          710 
## 8.898650e-01 2.390449e+00 2.245761e+00 2.542966e+00 2.245662e+00 
##          711          712          713          714          715 
## 2.105369e+00 1.112235e-01 2.245761e+00 2.404570e+00 1.018981e-02 
##          716          717          718          719          720 
## 2.516606e+00 1.119725e+00 1.047736e+00 2.796593e-01 2.421324e+00 
##          721          722          723          724          725 
## 2.325422e+00 2.328072e+00 2.442748e+00 1.804132e+00 1.700579e+00 
##          726          727          728          729          730 
## 3.906959e-01 1.102646e+00 2.243041e+00 2.426733e+00 1.211207e+00 
##          731          732          733          734          735 
## 2.444536e+00 1.730884e+00 6.219920e-02 2.177650e+00 1.516594e+00 
##          736          737          738          739          740 
## 7.244888e-01 1.086742e+00 1.528205e+00 1.842703e+00 1.900029e+00 
##          741          742          743          744          745 
## 2.525505e+00 5.371955e-01 1.947238e+00 2.041495e+00 2.176184e+00 
##          746          747          748          749          750 
## 2.544402e+00 2.266164e+00 2.161254e+00 2.526879e+00 6.530308e-01 
##          751          752          753          754          755 
## 1.322704e+00 2.324759e+00 1.318499e+00 2.535768e+00 2.283196e+00 
##          756          757          758          759          760 
## 1.102481e+00 1.449707e+00 2.060735e+00 2.540992e+00 2.324759e+00 
##          761          762          763          764          765 
## 8.804327e-01 2.466674e+00 1.596486e+00 1.153012e+00 2.326413e+00 
##          766          767          768          769          770 
## 6.284805e-01 6.968499e-01 2.467058e+00 1.211221e+00 1.842703e+00 
##          771          772          773          774          775 
## 1.527162e+00 2.525909e+00 1.086742e+00 1.729221e+00 7.956436e-01 
##          776          777          778          779          780 
## 1.971845e+00 1.718276e+00 2.563166e+00 4.355942e-01 1.655749e+00 
##          781          782          783          784          785 
## 2.320519e+00 2.532712e+00 2.152889e-01 2.541832e+00 2.328072e+00 
##          786          787          788          789          790 
## 1.578450e+00 2.134134e+00 2.493416e+00 2.269526e+00 2.197106e+00 
##          791          792          793          794          795 
## 4.467301e+00 2.088689e+00 2.525909e+00 4.927071e+00 1.928335e+00 
##          796          797          798          799          800 
## 2.516367e+00 2.319097e+00 1.808258e-01 1.527162e+00 1.869815e-01 
##          801          802          803          804          805 
## 1.886155e+00 1.157060e+00 2.019650e+00 1.579051e+00 2.112852e+00 
##          806          807          808          809          810 
## 6.924090e-01 1.730051e+00 2.041495e+00 3.450852e+00 2.557302e+00 
##          811          812          813          814          815 
## 1.676454e+00 2.198449e+00 1.424143e+00 2.533796e+00 7.674344e-01 
##          816          817          818          819          820 
## 2.292151e+00 1.509697e-01 2.509957e+00 1.973032e+00 2.201446e+00 
##          821          822          823          824          825 
## 2.458017e+00 2.058626e+00 5.648587e-01 1.527973e-01 2.546280e+00 
##          826          827          828          829          830 
## 9.370776e-01 6.824252e-01 1.654313e+00 2.293531e+00 1.096250e+00 
##          831          832          833          834          835 
## 1.869815e-01 1.700579e+00 1.075349e+00 2.151590e+00 2.155243e+00 
##          836          837          838          839          840 
## 2.406316e+00 2.446329e+00 2.178011e-01 9.924011e-01 2.532712e+00 
##          841          842          843          844          845 
## 8.573311e-01 2.715932e-01 4.738952e-01 1.825994e-01 1.324803e+00 
##          846          847          848          849          850 
## 2.135548e+00 2.134134e+00 9.366349e-01 2.465012e+00 3.614232e-01 
##          851          852          853          854          855 
## 2.306489e+00 2.176184e+00 4.042588e-01 2.528647e+00 1.730051e+00 
##          856          857          858          859          860 
## 2.561304e+00 1.876241e+00 1.925932e+00 1.358541e+00 1.945157e+00 
##          861          862          863          864          865 
## 3.568420e+00 5.648587e-01 6.192300e+00 3.011211e-01 1.232192e-01 
##          866          867          868          869          870 
## 3.529126e+00 4.693861e-01 4.833181e+00 1.291763e+00 1.528205e+00 
##          871          872          873          874          875 
## 2.847248e+00 2.367499e+00 7.956436e-01 4.503304e-01 1.238118e+00 
##          876          877          878          879          880 
## 1.075349e+00 2.697999e+00 1.075139e+00 3.700368e+00 3.482170e-01 
##          881          882          883          884          885 
## 5.004168e+00 1.419193e+00 6.845083e+00 7.789262e+00 1.172649e+01 
##          886          887          888          889          890 
## 1.735255e+00 1.779844e+00 1.700579e+00 2.660929e+00 3.821092e-01 
##          891          892          893          894          895 
## 7.212589e+00 2.036007e+00 4.395454e+00 7.212589e+00 5.004168e+00 
##          896          897          898          899          900 
## 3.256977e+00 3.418111e-01 2.104254e+00 6.192300e+00 8.244252e-01 
##          901          902          903          904          905 
## 3.906959e-01 3.489937e+00 2.266056e+00 3.084915e-02 1.948389e+00 
##          906          907          908          909          910 
## 4.961243e+00 5.886795e+00 1.020273e+00 1.538369e-01 3.180143e+00 
##          911          912          913          914          915 
## 5.753110e+00 5.207131e+00 4.718410e+00 2.112852e+00 6.314788e+00 
##          916          917          918          919          920 
## 5.500298e+00 4.676204e+00 5.152659e+00 5.633546e+00 5.753110e+00 
##          921          922          923          924          925 
## 7.789262e+00 6.940765e+00 1.874836e+00 2.328072e+00 2.556687e+00 
##          926          927          928          929          930 
## 6.625282e+00 4.071313e-01 1.464667e-03 2.014510e+00 1.825994e-01 
##          931          932          933          934          935 
## 1.075139e+00 2.429917e+00 8.359896e+00 6.361176e+00 6.454355e+00 
##          936          937          938          939          940 
## 6.192300e+00 2.266056e+00 3.568420e+00 8.244252e-01 5.633546e+00 
##          941          942          943          944          945 
## 1.020273e+00 1.066244e+01 9.224781e-01 1.020796e+00 4.108082e+00 
##          946          947          948          949          950 
## 6.604063e-01 2.286406e+00 2.198449e+00 1.735255e+00 3.411871e+00 
##          951          952          953          954          955 
## 1.562739e+00 1.285318e-01 8.860740e-02 5.892532e-01 5.163714e+00 
##          956          957          958          959          960 
## 4.189631e+00 5.544589e+00 2.051308e+00 6.845083e+00 2.879617e-02 
##          961          962          963          964          965 
## 2.517372e+00 5.843102e+00 3.372994e+00 9.924011e-01 1.324803e+00 
##          966          967          968          969          970 
## 5.163714e+00 3.489937e+00 3.180143e+00 1.210443e-01 7.617314e+00 
##          971          972          973          974          975 
## 5.250671e+00 2.559448e+00 2.122526e+00 5.500298e+00 5.500298e+00 
##          976          977          978          979          980 
## 7.617314e+00 2.772429e+00 1.874836e+00 3.529126e+00 6.845083e+00 
##          981          982          983          984          985 
## 3.489937e+00 2.513603e+00 1.228701e+00 1.344713e+00 2.199945e+00 
##          986          987          988          989          990 
## 5.250671e+00 5.798042e+00 3.836255e+00 4.108082e+00 6.284805e-01 
##          991          992          993          994          995 
## 6.988815e+00 4.718410e+00 2.266056e+00 3.180143e+00 4.189631e+00 
##          996          997          998          999         1000 
## 2.051308e+00 6.314788e+00 8.659563e+00 1.874836e+00 6.100472e+00 
##         1001         1002         1003         1004         1005 
## 2.884804e+00 7.261358e+00 2.798928e-01 4.634115e+00 7.212589e+00 
##         1006         1007         1008         1009         1010 
## 6.314788e+00 1.973032e+00 7.212589e+00 2.922458e+00 1.553696e+00 
##         1011         1012         1013         1014         1015 
## 1.264970e+00 5.294332e+00 4.108082e+00 7.438679e+00 1.805076e+00 
##         1016         1017         1018         1019         1020 
## 2.199945e+00 6.672491e+00 5.207131e+00 2.065793e+00 6.437087e-04 
##         1021         1022         1023         1024         1025 
## 2.064476e+00 1.821672e+00 9.636965e-01 2.466674e+00 2.015834e+00 
##         1026         1027         1028         1029         1030 
## 4.592141e+00 2.442748e+00 1.677016e+00 2.521602e+00 6.625282e+00 
##         1031         1032         1033         1034         1035 
## 2.809790e+00 2.055413e+00 2.112852e+00 3.084915e-02 2.922458e+00 
##         1036         1037         1038         1039         1040 
## 1.018981e-02 5.544589e+00 3.179637e-02 7.888814e-01 7.168763e-01 
##         1041         1042         1043         1044         1045 
## 2.548163e+00 6.021656e+00 1.665989e+00 2.341970e+00 7.438679e+00 
##         1046         1047         1048         1049         1050 
## 2.477009e+00 9.643740e-01 1.075349e+00 1.086742e+00 3.372994e+00 
##         1051         1052         1053         1054         1055 
## 1.874836e+00 4.385262e-01 5.888291e+00 4.592141e+00 6.719837e+00 
##         1056         1057         1058         1059         1060 
## 1.157134e+00 6.940765e+00 2.123326e-01 7.115479e+00 2.531403e+00 
##         1061         1062         1063         1064         1065 
## 2.123326e-01 3.614232e-01 3.074065e+00 3.074065e+00 5.843102e+00 
##         1066         1067         1068         1069         1070 
## 1.926577e+00 1.878342e+00 3.139931e-01 5.004168e+00 8.616600e+00 
##         1071         1072         1073         1074         1075 
## 9.551707e-01 2.178011e-01 1.874836e+00 5.083064e-01 8.804327e-01 
##         1076         1077         1078         1079         1080 
## 3.607818e+00 2.230036e+00 2.486936e-01 3.796311e+00 6.892854e+00 
##         1081         1082         1083         1084         1085 
## 2.957318e+00 2.478521e+00 5.456132e+00 7.261358e+00 5.798042e+00 
##         1086         1087         1088         1089         1090 
## 1.730884e+00 9.454899e+00 4.108082e+00 2.544402e+00 2.241096e+00 
##         1091         1092         1093         1094         1095 
## 2.152889e-01 3.997110e+00 3.796311e+00 2.288019e+00 2.697999e+00 
##         1096         1097         1098         1099         1100 
## 6.454355e+00 5.250671e+00 1.527162e+00 3.450852e+00 2.488914e+00 
##         1101         1102         1103         1104         1105 
## 7.488035e+00 6.192300e+00 2.067114e+00 7.212589e+00 6.454355e+00 
##         1106         1107         1108         1109         1110 
## 5.456132e+00 5.047213e+00 2.502629e+00 6.314788e+00 9.643740e-01 
##         1111         1112         1113         1114         1115 
## 5.633546e+00 6.578209e+00 1.825994e-01 3.180143e+00 2.557302e+00 
##         1116         1117         1118         1119         1120 
## 2.086872e+00 5.294332e+00 4.490404e-01 1.170942e+00 4.698636e+00 
##         1121         1122         1123         1124         1125 
## 6.940765e+00 2.288019e+00 2.735166e+00 6.845083e+00 7.602017e-01 
##         1126         1127         1128         1129         1130 
## 3.956733e+00 2.513603e+00 6.625282e+00 6.054754e+00 6.845083e+00 
##         1131         1132         1133         1134         1135 
## 7.389467e+00 4.833181e+00 6.146320e+00 6.940765e+00 7.389467e+00 
##         1136         1137         1138         1139         1140 
## 1.086742e+00 5.331621e-01 2.385258e+00 4.354065e+00 1.232192e-01 
##         1141         1142         1143         1144         1145 
## 1.845267e-01 3.756475e+00 3.334219e+00 5.047213e+00 4.354065e+00 
##         1146         1147         1148         1149         1150 
## 1.324803e+00 8.248761e-01 1.654313e+00 1.804132e+00 5.633546e+00 
##         1151         1152         1153         1154         1155 
## 3.836255e+00 4.230571e+00 1.318310e+00 4.108082e+00 5.843102e+00 
##         1156         1157         1158         1159         1160 
## 3.074065e+00 2.015834e+00 5.371955e-01 1.805076e+00 1.211207e+00 
##         1161         1162         1163         1164         1165 
## 6.284805e-01 5.371955e-01 2.152889e-01 5.544589e+00 1.058108e+00 
##         1166         1167         1168         1169         1170 
## 3.256977e+00 6.054754e+00 1.246326e+00 6.192300e+00 1.303534e+00 
##         1171         1172         1173         1174         1175 
## 1.020796e+00 2.431516e+00 6.625282e+00 3.489937e+00 2.526879e+00 
##         1176         1177         1178         1179         1180 
## 6.192300e+00 1.246326e+00 4.148801e+00 7.667120e+00 1.475929e+00 
##         1181         1182         1183         1184         1185 
## 4.918438e+00 1.839809e+00 2.338375e+00 5.047213e+00 3.489937e+00 
##         1186         1187         1188         1189         1190 
## 2.283196e+00 1.075139e+00 7.717073e+00 2.548163e+00 8.573311e-01 
##         1191         1192         1193         1194         1195 
## 1.945157e+00 2.273583e+00 3.106983e-01 2.847248e+00 2.065793e+00 
##         1196         1197         1198         1199         1200 
## 9.366349e-01 2.194108e+00 2.623954e+00 2.194108e+00 1.945157e+00 
##         1201         1202         1203         1204         1205 
## 1.020796e+00 2.486936e-01 5.331621e-01 4.918438e+00 1.426269e+00 
##         1206         1207         1208         1209         1210 
## 2.523716e+00 3.529126e+00 5.843102e+00 2.502629e+00 1.902199e+00 
##         1211         1212         1213         1214         1215 
## 7.212589e+00 1.909952e+00 1.948389e+00 4.189631e+00 1.562739e+00 
##         1216         1217         1218         1219         1220 
## 2.427272e+00 1.517330e+00 1.426269e+00 9.370776e-01 4.148801e+00 
##         1221         1222         1223         1224         1225 
## 6.530308e-01 6.146320e+00 4.718410e+00 6.539609e-01 9.366349e-01 
##         1226         1227         1228         1229         1230 
## 3.836255e+00 2.525115e+00 2.534526e+00 2.439187e+00 2.201446e+00 
##         1231         1232         1233         1234         1235 
## 5.047213e+00 2.051308e+00 9.672285e-01 2.552073e+00 6.054754e+00 
##         1236         1237         1238         1239         1240 
## 8.248761e-01 7.488035e+00 1.909952e+00 7.566462e-01 2.715932e-01 
##         1241 
## 2.051308e+00
mean(Error1)
## [1] 2.481516
sd(Error1)
## [1] 1.841579
  • Suma de cuadrados de los residuales
sqrt(sum(Residuales1^2)/summary(mod1)$df[2])
## [1] 0.6222003

AIC

AIC(mod1)
## [1] 2348.112

Modelo cuadrático (Modelos 2)

mod2 <- lm(Ht~DAP_cm+I(DAP_cm^2),datos)
summary(mod2)
## 
## Call:
## lm(formula = Ht ~ DAP_cm + I(DAP_cm^2), data = datos)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.36854 -0.08481  0.04423  0.10650  1.28200 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  7.369e+00  2.001e-02   368.2   <2e-16 ***
## DAP_cm       6.683e-01  1.499e-03   445.8   <2e-16 ***
## I(DAP_cm^2) -3.379e-03  2.384e-05  -141.7   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.15 on 1238 degrees of freedom
## Multiple R-squared:  0.9989, Adjusted R-squared:  0.9989 
## F-statistic: 5.458e+05 on 2 and 1238 DF,  p-value: < 2.2e-16
{par(mfrow=c(2,2))
plot(mod2)}

  • Análisis de varianza para el modelo cuadrático
anova(mod2)
## Analysis of Variance Table
## 
## Response: Ht
##               Df  Sum Sq Mean Sq F value    Pr(>F)    
## DAP_cm         1 24099.9 24099.9 1071599 < 2.2e-16 ***
## I(DAP_cm^2)    1   451.8   451.8   20090 < 2.2e-16 ***
## Residuals   1238    27.8     0.0                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
  • Residuales vs Predichos
Residuales2 <- residuals(mod2)
predichos2 <- predict(mod2)
plot(Residuales2~predichos2, main = "Residuales Vs Predichos Modelo Cuadrático")

ggplot(mod2, aes(predichos2, mod2$residuals)) +
   geom_point() +
   geom_smooth(method = "lm")

  • Verificamos la normalidad de los residuales
shapiro.test(Residuales2)
## 
##  Shapiro-Wilk normality test
## 
## data:  Residuales2
## W = 0.83838, p-value < 2.2e-16
  • Cálculo del error
#  Error absoluto
Error2 <- abs(((predichos2-datos$Ht)/datos$Ht)*100)
Error2
##            1            2            3            4            5 
## 0.1436636722 0.6488590894 0.4350540289 0.5974643564 0.2583926671 
##            6            7            8            9           10 
## 0.6668302689 0.6856725143 0.3824280920 0.0672326833 0.6897321560 
##           11           12           13           14           15 
## 0.3418819069 0.3285890016 0.1883777018 0.5546400404 0.2131275985 
##           16           17           18           19           20 
## 0.5385537300 0.6103195287 0.2048285471 0.4836617493 0.1040930327 
##           21           22           23           24           25 
## 0.0934358790 0.2131275985 0.6887739042 0.0299420205 0.3064536463 
##           26           27           28           29           30 
## 0.0799466612 0.0606692025 0.6604938533 0.0963231645 0.3022958773 
##           31           32           33           34           35 
## 0.2572221218 0.6410688530 0.3962861302 0.3918732542 0.3582591754 
##           36           37           38           39           40 
## 0.6157810679 0.6956989387 0.1946544040 0.6032426066 0.5950561820 
##           41           42           43           44           45 
## 0.6610124617 0.4009689898 0.2031454394 0.5227023489 0.6170564763 
##           46           47           48           49           50 
## 0.6537725602 0.3418819069 0.7016444889 0.0799466612 0.2389103113 
##           51           52           53           54           55 
## 1.0163842185 0.7044370927 0.3064536463 0.5860954725 0.2760430590 
##           56           57           58           59           60 
## 0.6735162668 0.5223301857 0.2478335921 0.6488590894 0.3524531678 
##           61           62           63           64           65 
## 0.0043802849 0.2385961875 0.6338238369 0.2764550604 0.2385961875 
##           66           67           68           69           70 
## 0.4090422955 0.1508065285 0.4713708554 0.6220719228 0.4526540489 
##           71           72           73           74           75 
## 0.6968726978 0.5063683859 0.3353962185 0.6284486157 0.9618107541 
##           76           77           78           79           80 
## 0.6638466830 0.0287818808 0.7466372448 0.1219554375 0.2783324295 
##           81           82           83           84           85 
## 0.2295092865 0.6690569652 0.0688568088 0.0872832884 0.0976052627 
##           86           87           88           89           90 
## 0.2764550604 0.6975851211 0.3467476441 0.0494996363 0.0180520128 
##           91           92           93           94           95 
## 0.2764550604 0.6220719228 0.1966760861 0.7131671029 0.2478017569 
##           96           97           98           99          100 
## 0.0043802849 0.4915369444 0.2667624017 0.5070303483 0.2885338301 
##          101          102          103          104          105 
## 0.4385547073 0.2205722708 0.3885949935 0.1808085518 0.7016444889 
##          106          107          108          109          110 
## 0.5877239174 0.3353962185 0.6440943681 0.4246268841 0.4762213581 
##          111          112          113          114          115 
## 0.7096442702 0.0239371148 0.5793385791 0.1879278257 0.4906383410 
##          116          117          118          119          120 
## 0.4262112389 0.1298031066 0.4762213581 0.1319840557 0.5877239174 
##          121          122          123          124          125 
## 0.9708365815 0.3638684231 0.6504882020 0.0337599856 0.5726007149 
##          126          127          128          129          130 
## 0.5771828461 0.7058371381 0.6296685807 0.0688568088 0.3817652613 
##          131          132          133          134          135 
## 0.5389031298 0.1319840557 0.3780003280 0.6512269030 0.6001923638 
##          136          137          138          139          140 
## 0.2086508325 0.1580918653 0.4959886231 0.7077877593 0.0299420205 
##          141          142          143          144          145 
## 0.1863108146 0.1655202605 0.3285890016 0.3836954889 0.5579078791 
##          146          147          148          149          150 
## 0.2131275985 0.3802677201 0.3272262774 0.2928130163 0.2117845256 
##          151          152          153          154          155 
## 0.1436636722 0.3300754158 0.1040930327 0.3417080158 0.2215738403 
##          156          157          158          159          160 
## 0.6440943681 0.6735162668 0.1467836173 0.1269265207 0.5726007149 
##          161          162          163          164          165 
## 0.0743338423 0.7154874435 0.1655202605 0.0976052627 0.6187644948 
##          166          167          168          169          170 
## 0.6361448379 0.6956989387 0.2486530274 0.3643258854 1.1296686144 
##          171          172          173          174          175 
## 0.4942142060 0.6001923638 0.6835760687 0.1100665998 0.1366627220 
##          176          177          178          179          180 
## 0.1959253002 0.1621587232 0.3094028915 0.9498940099 0.5950561820 
##          181          182          183          184          185 
## 0.1857370412 0.2131275985 0.1610023798 0.3962861302 0.6187148292 
##          186          187          188          189          190 
## 0.1959253002 0.2764550604 0.4713708554 0.2550199757 0.1580918653 
##          191          192          193          194          195 
## 0.1100665998 0.6635493174 0.0239371148 0.1393121850 0.1366627220 
##          196          197          198          199          200 
## 0.5726007149 0.2326012774 0.6692371056 0.5899560716 0.6316287496 
##          201          202          203          204          205 
## 0.3817652613 0.1808085518 0.2215738403 0.1037666697 0.6284486157 
##          206          207          208          209          210 
## 0.0372232949 0.6066175113 0.3291685400 0.0856958074 0.2495956436 
##          211          212          213          214          215 
## 0.6456039557 0.7132341364 0.1040930327 0.3763848190 0.2549407954 
##          216          217          218          219          220 
## 0.6544872975 0.4009689898 0.5726007149 0.6753883059 0.7058371381 
##          221          222          223          224          225 
## 0.4219646915 0.2880891304 0.5911898417 0.1808085518 0.3530243231 
##          226          227          228          229          230 
## 0.1245030312 0.6753883059 0.6968726978 0.0337599856 0.6893745877 
##          231          232          233          234          235 
## 1.1455749872 0.3407303171 0.2783324295 0.5385537300 0.2915781944 
##          236          237          238          239          240 
## 0.1366627220 0.5818124075 0.6834862764 0.2682855888 0.6296685807 
##          241          242          243          244          245 
## 0.7891246958 0.1781140696 0.6289696604 0.2385961875 0.6440379322 
##          246          247          248          249          250 
## 0.1655202605 0.4836617493 0.0287818808 0.4501902855 0.2131275985 
##          251          252          253          254          255 
## 0.7231228369 0.4584291207 0.7019462323 0.0419342273 0.9910038567 
##          256          257          258          259          260 
## 0.4694454081 0.6628517321 0.5410612176 0.2568428256 0.4957281692 
##          261          262          263          264          265 
## 0.2568428256 0.1808085518 0.7026886852 0.3530243231 0.6740544821 
##          266          267          268          269          270 
## 0.1319840557 0.7114303844 0.6887739042 0.5406597269 0.2682855888 
##          271          272          273          274          275 
## 0.0092637476 0.6815538732 0.1088889218 0.6187148292 0.2117845256 
##          276          277          278          279          280 
## 0.3643377734 0.7102409776 0.6032426066 0.0974727935 0.7019462323 
##          281          282          283          284          285 
## 0.4813702586 0.4447805660 0.3909457765 0.3500922525 0.4090422955 
##          286          287          288          289          290 
## 0.1269265207 0.1319840557 0.4729339595 0.4350540289 0.2782023360 
##          291          292          293          294          295 
## 1.5868340551 1.8309491857 1.7181767115 1.1259812244 0.2388301496 
##          296          297          298          299          300 
## 0.6831229409 1.8018848904 0.6440943681 0.4501902855 0.0228432922 
##          301          302          303          304          305 
## 0.3838077040 1.1641953469 0.0077007697 0.5029994698 0.4090422955 
##          306          307          308          309          310 
## 0.6208731515 0.0049880716 0.6257934624 0.7725785909 0.4501941310 
##          311          312          313          314          315 
## 0.2603767345 0.4527335316 0.1378317566 1.3454787635 0.6372027475 
##          316          317          318          319          320 
## 0.1837242267 0.7096442702 0.5899560716 0.4134629066 0.3418819069 
##          321          322          323          324          325 
## 0.5410612176 0.5291688659 0.2047525135 0.5528107955 0.5407675153 
##          326          327          328          329          330 
## 0.6361448379 0.1106484944 0.6032426066 0.4843242908 0.5687868370 
##          331          332          333          334          335 
## 0.5227023489 0.3860869495 0.4495196273 0.8993550585 0.3647946589 
##          336          337          338          339          340 
## 0.4933009445 0.5175831712 0.2711733649 1.1224335300 0.4447805660 
##          341          342          343          344          345 
## 0.4915369444 0.4625025234 0.6622239170 1.1163792013 0.1627619718 
##          346          347          348          349          350 
## 0.6372027475 2.1441076820 0.6666772293 0.7295181311 0.4625025234 
##          351          352          353          354          355 
## 1.8212827943 0.6815538732 0.2152912651 0.2280803102 0.0692623989 
##          356          357          358          359          360 
## 0.3022958773 0.6440943681 1.0267104204 0.6575545802 1.0603855699 
##          361          362          363          364          365 
## 0.5222781562 1.1871794765 1.0650451708 0.4350540289 0.2928130163 
##          366          367          368          369          370 
## 0.1621587232 0.3418819069 0.4083631765 1.8115946642 0.4195227979 
##          371          372          373          374          375 
## 0.4755339342 0.7986760786 2.1539104450 0.3918732542 0.4729339595 
##          376          377          378          379          380 
## 0.2468743296 0.2388301496 0.3799819190 1.8309491857 0.7102409776 
##          381          382          383          384          385 
## 0.5883013131 0.5640034965 0.2863007298 0.0133973480 0.6977586048 
##          386          387          388          389          390 
## 0.2084685762 0.5590000206 0.1334571388 0.5911664423 0.5881342110 
##          391          392          393          394          395 
## 0.9910038567 1.3454787635 0.6977586048 0.7841318544 0.9960937726 
##          396          397          398          399          400 
## 0.3909457765 0.5726007149 0.8705469428 0.6887739042 0.9342042059 
##          401          402          403          404          405 
## 0.4418847995 0.2603767345 0.6690569652 2.0293265344 0.2284857371 
##          406          407          408          409          410 
## 0.4418847995 0.5071455466 0.5661257194 1.0075693146 1.9249962641 
##          411          412          413          414          415 
## 0.1210375485 0.0126796547 0.6103195287 1.0521197938 0.4646905879 
##          416          417          418          419          420 
## 0.5406597269 0.6638466830 0.6504882020 0.4275090724 1.1830615788 
##          421          422          423          424          425 
## 1.0261103852 0.4275090724 0.4439652747 0.2084685762 2.1921875549 
##          426          427          428          429          430 
## 1.0848273092 0.2152912651 0.0431170773 0.6704493611 0.2583720000 
##          431          432          433          434          435 
## 0.1883777018 1.2257960280 0.3860869495 0.2301678757 1.5868340551 
##          436          437          438          439          440 
## 1.1296686144 0.6565704518 0.4331369956 0.4729339595 0.0486723292 
##          441          442          443          444          445 
## 0.2047525135 0.4643034726 0.1523057612 0.6257934624 0.4959886231 
##          446          447          448          449          450 
## 0.6929854670 0.1378317566 0.4955970794 1.0106294502 0.2470052215 
##          451          452          453          454          455 
## 0.4195227979 1.5771793083 1.8309491857 0.6735162668 0.6905101180 
##          456          457          458          459          460 
## 2.1539104450 0.6956989387 0.5029994698 0.5686468365 0.4530870775 
##          461          462          463          464          465 
## 0.5964746897 0.2215738403 0.7231228369 2.1921875549 0.8167420027 
##          466          467          468          469          470 
## 0.2104325393 0.6966138379 0.2759234796 0.7146468278 0.4750504057 
##          471          472          473          474          475 
## 1.3454787635 0.6975851211 0.6289696604 0.0934358790 0.4331369956 
##          476          477          478          479          480 
## 0.1314434866 0.6628517321 1.6988783683 0.6765899240 0.7533494443 
##          481          482          483          484          485 
## 0.5546400404 0.6856725143 1.3551049283 0.4530145013 1.0372701278 
##          486          487          488          489          490 
## 0.6956989387 0.0419342273 0.6767848118 0.8028542030 1.2012238385 
##          491          492          493          494          495 
## 0.4713708554 0.5881342110 0.3338744619 0.5293241592 0.3253876213 
##          496          497          498          499          500 
## 0.3417080158 1.1004218655 0.9636912915 0.3471801236 0.6257934624 
##          501          502          503          504          505 
## 0.4843242908 0.5542286063 2.0390968437 0.6001923638 1.1189719280 
##          506          507          508          509          510 
## 0.6316287496 0.2390660359 0.3471801236 0.2066278271 0.6871054543 
##          511          512          513          514          515 
## 0.6884171009 0.6783091693 0.4501902855 0.3712696690 0.6586953020 
##          516          517          518          519          520 
## 1.8309491857 0.8897730690 0.0077007697 0.5115091565 1.0258715293 
##          521          522          523          524          525 
## 1.0171503637 0.3515499065 0.4388447310 0.4418847995 0.3036559238 
##          526          527          528          529          530 
## 1.2354201459 0.5410612176 0.5590000206 0.6735797620 0.7024897756 
##          531          532          533          534          535 
## 0.5410612176 2.0293265344 0.1106484944 0.0024982781 2.5762404972 
##          536          537          538          539          540 
## 0.1942301470 0.4306966893 0.5927411794 0.1844628668 0.6835760687 
##          541          542          543          544          545 
## 0.7437042057 0.0336468612 0.5806881835 0.1984323173 0.8897730690 
##          546          547          548          549          550 
## 0.3690329880 0.1418662452 0.6887739042 1.1478100487 0.5389031298 
##          551          552          553          554          555 
## 0.3036559238 0.6966781290 0.4915369444 1.0139802381 1.2298457877 
##          556          557          558          559          560 
## 3.2316705771 0.4278250492 1.1237109952 0.2880891304 0.2470052215 
##          561          562          563          564          565 
## 0.6628517321 0.4828550435 0.2928130163 2.0488454002 0.4090422955 
##          566          567          568          569          570 
## 0.0101976029 0.1581044263 0.3417080158 0.2470052215 0.5423435911 
##          571          572          573          574          575 
## 0.2258463407 0.2364176796 0.0688568088 0.0692623989 1.1455749872 
##          576          577          578          579          580 
## 0.1210375485 0.1378317566 0.0795832758 0.3690329880 1.2354201459 
##          581          582          583          584          585 
## 0.2337871520 0.1479770934 0.6829135679 1.5771793083 1.1866585963 
##          586          587          588          589          590 
## 0.3272262774 0.6753883059 0.1837242267 0.5780348884 0.0077007697 
##          591          592          593          594          595 
## 0.1353889743 0.8897730690 0.2743065214 0.1783048009 0.5636237644 
##          596          597          598          599          600 
## 0.2066278271 0.7533494443 0.4429449964 0.1276684855 0.7116903206 
##          601          602          603          604          605 
## 1.3551049283 0.8854404782 0.7026886852 0.2782023360 1.2106794863 
##          606          607          608          609          610 
## 0.4447805660 0.2821651378 0.3580990380 1.2546048799 1.9152569347 
##          611          612          613          614          615 
## 1.1163792013 0.9087513737 0.2979569096 0.2979569096 1.7085383790 
##          616          617          618          619          620 
## 1.0848273092 0.1627619718 0.0024982781 1.1167208181 0.4755339342 
##          621          622          623          624          625 
## 0.6638985782 0.6575545802 0.4915369444 0.4142920329 0.2682966011 
##          626          627          628          629          630 
## 0.6831229409 1.1635738535 0.3643377734 0.2667624017 0.6509521671 
##          631          632          633          634          635 
## 0.3145316475 0.4906383410 0.4388447310 0.5384841700 0.4829042727 
##          636          637          638          639          640 
## 0.0431170773 0.1580918653 0.5063683859 0.3817652613 0.4526540489 
##          641          642          643          644          645 
## 0.6018892275 0.7357704341 0.2547461955 0.0126796547 0.6018892275 
##          646          647          648          649          650 
## 0.5881342110 1.2098350995 0.2335081269 0.6956989387 0.6961813282 
##          651          652          653          654          655 
## 0.5556597015 0.0385011464 0.6969654416 0.4385547073 0.2611153140 
##          656          657          658          659          660 
## 0.6468886427 0.7704352286 0.1334571388 0.5389031298 0.7077877593 
##          661          662          663          664          665 
## 0.4313014250 0.0733137435 0.6066175113 0.6692299521 0.6693938065 
##          666          667          668          669          670 
## 0.6815538732 0.6440379322 0.3643258854 0.6157810679 0.4584291207 
##          671          672          673          674          675 
## 0.1700635709 0.2495956436 0.4906383410 0.1230842575 0.0419342273 
##          676          677          678          679          680 
## 0.3064536463 0.4035969720 0.2131275985 0.4530870775 0.1942301470 
##          681          682          683          684          685 
## 0.5793385791 0.6628517321 0.0990850945 0.1844628668 0.2682855888 
##          686          687          688          689          690 
## 0.6831229409 0.8028542030 0.3285890016 0.6694716744 0.0571601798 
##          691          692          693          694          695 
## 0.5389031298 0.3590079716 0.0635150221 0.6638466830 0.6929854670 
##          696          697          698          699          700 
## 0.5451186142 0.6385908865 0.5291688659 0.5451186142 0.3836954889 
##          701          702          703          704          705 
## 0.2478017569 0.2486530274 0.6296685807 0.1576784631 0.6235122054 
##          706          707          708          709          710 
## 0.3471801236 0.5385537300 0.6157810679 0.1580918653 0.2550199757 
##          711          712          713          714          715 
## 0.3666597772 1.0903759714 0.6157810679 0.4776479770 1.1172375802 
##          716          717          718          719          720 
## 0.1177553927 1.2134828812 0.6767848118 0.4843242908 0.0671304587 
##          721          722          723          724          725 
## 0.5728190442 0.5556597015 0.4526540489 0.6835760687 0.1314434866 
##          726          727          728          729          730 
## 0.6048057840 0.6740544821 0.2548338168 0.0672326833 0.6704493611 
##          731          732          733          734          735 
## 0.4669256506 0.7116903206 0.5291688659 0.6066175113 0.6808356741 
##          736          737          738          739          740 
## 0.3638684231 0.2819854778 0.7250810761 0.5297808993 0.6512269030 
##          741          742          743          744          745 
## 0.1543989349 0.6330891677 0.6372027475 0.6338238369 0.5877239174 
##          746          747          748          749          750 
## 0.3418819069 0.5950561820 0.5996125124 0.0976052627 0.6504882020 
##          751          752          753          754          755 
## 0.7765925667 0.5223301857 0.7235150629 0.1298031066 0.5406597269 
##          756          757          758          759          760 
## 0.7026886852 0.6841085000 0.3997506501 1.1665520016 0.5223301857 
##          761          762          763          764          765 
## 0.6887739042 0.0003701466 0.6529543372 0.2603767345 0.5389031298 
##          766          767          768          769          770 
## 0.3972178764 0.9740326735 0.4836617493 0.6982599557 0.5297808993 
##          771          772          773          774          775 
## 0.6739795357 0.2390660359 0.2819854778 0.6640485305 0.6815538732 
##          776          777          778          779          780 
## 0.6520141419 0.5974591325 0.2478017569 0.4275090724 0.7183708266 
##          781          782          783          784          785 
## 0.1857370412 0.1863108146 0.4713708554 0.2295092865 0.5556597015 
##          786          787          788          789          790 
## 0.6765899240 0.6339627716 0.3836954889 0.2335081269 0.2948675970 
##          791          792          793          794          795 
## 0.7992947010 0.6435554692 0.2390660359 0.6937776671 0.4828550435 
##          796          797          798          799          800 
## 0.0635150221 0.1868918760 0.5881342110 0.6739795357 0.5185763752 
##          801          802          803          804          805 
## 0.5115091565 0.7001653489 0.6604938533 0.7016444889 0.6586664028 
##          806          807          808          809          810 
## 0.3749704476 0.6877599135 0.6338238369 0.4429449964 0.1697733654 
##          811          812          813          814          815 
## 0.6068578022 0.5846067170 0.7231228369 0.3937611784 0.6690569652 
##          816          817          818          819          820 
## 0.2117433819 0.5763473355 0.3643377734 0.6735162668 0.6220719228 
##          821          822          823          824          825 
## 0.4142920329 0.3949511187 0.4195227979 0.5423435911 0.3530243231 
##          826          827          828          829          830 
## 0.6544872975 0.6316287496 0.6693938065 0.2111465950 0.8520512825 
##          831          832          833          834          835 
## 0.5185763752 0.1314434866 0.6610124617 0.3327185567 0.6103195287 
##          836          837          838          839          840 
## 0.4927296097 0.4813702586 0.5071455466 0.6801432488 0.1863108146 
##          841          842          843          844          845 
## 0.3580990380 0.5899560716 0.4212850432 0.5542286063 0.2470052215 
##          846          847          848          849          850 
## 0.6537725602 0.6339627716 0.6841371294 0.0049880716 0.5927411794 
##          851          852          853          854          855 
## 0.5566290899 0.5877239174 0.4388447310 0.1037666697 0.6877599135 
##          856          857          858          859          860 
## 0.2389103113 0.6587724093 0.6879478553 0.2364176796 0.0589587282 
##          861          862          863          864          865 
## 0.4722518934 0.4195227979 1.4946426569 0.6018892275 0.5060104768 
##          866          867          868          869          870 
## 0.4625025234 1.0179812953 0.9787010837 0.7102360733 0.7250810761 
##          871          872          873          874          875 
## 0.2384664947 0.5222781562 0.6815538732 0.5964746897 0.6837031950 
##          876          877          878          879          880 
## 0.6610124617 0.1984323173 0.6897321560 0.9864149548 1.0520027323 
##          881          882          883          884          885 
## 1.0171503637 0.7350368562 1.8018848904 2.1921875549 2.9417453621 
##          886          887          888          889          890 
## 0.1210375485 0.6925757906 0.1314434866 0.1883777018 1.1617817519 
##          891          892          893          894          895 
## 1.9347138935 0.4088516259 0.7725785909 1.9347138935 1.0171503637 
##          896          897          898          899          900 
## 0.3937118792 0.4615572234 0.3647946589 1.4946426569 0.6635493174 
##          901          902          903          904          905 
## 0.6048057840 0.4527335316 0.0329891226 0.5293241592 0.6587746504 
##          906          907          908          909          910 
## 1.0075693146 0.3765634391 0.6638466830 0.4944508286 0.3738845218 
##          911          912          913          914          915 
## 1.3454787635 1.1163792013 0.8993550585 0.6586664028 1.5771793083 
##          916          917          918          919          920 
## 1.2354201459 0.8897730690 0.6298183755 1.2641653163 1.3454787635 
##          921          922          923          924          925 
## 2.1921875549 1.8212827943 0.0795832758 0.5556597015 0.3064536463 
##          926          927          928          929          930 
## 1.6988783683 0.4755339342 0.5523790739 0.4250061965 0.5542286063 
##          931          932          933          934          935 
## 0.6897321560 0.0606451289 0.7627735707 1.5868340551 1.6060788910 
##          936          937          938          939          940 
## 1.4946426569 0.0329891226 0.4722518934 0.6635493174 1.2641653163 
##          941          942          943          944          945 
## 0.6638466830 2.1927721699 0.3362762996 0.3036559238 0.7049207558 
##          946          947          948          949          950 
## 0.3860869495 0.5753428464 0.5846067170 0.1210375485 0.4331369956 
##          951          952          953          954          955 
## 0.1732348143 1.0802983463 1.1244347565 1.1740912816 1.1067562003 
##          956          957          958          959          960 
## 0.7243528148 1.2450231264 0.0281516095 1.8018848904 0.5640034965 
##          961          962          963          964          965 
## 0.4135075047 1.3647097963 0.4233096066 0.6801432488 0.2470052215 
##          966          967          968          969          970 
## 1.1067562003 0.4527335316 0.3738845218 0.5645728493 2.1342832140 
##          971          972          973          974          975 
## 1.1259812244 0.2301678757 0.0077007697 1.2354201459 1.2354201459 
##          976          977          978          979          980 
## 2.1342832140 0.2184864069 0.0795832758 0.4625025234 1.8018848904 
##          981          982          983          984          985 
## 0.4527335316 0.1479770934 1.2361220567 0.6827224070 0.6032426066 
##          986          987          988          989          990 
## 1.1259812244 1.3551049283 0.5883013131 0.7049207558 0.3972178764 
##          991          992          993          994          995 
## 1.8309491857 0.8993550585 0.0329891226 0.3738845218 0.7243528148 
##          996          997          998          999         1000 
## 0.0281516095 1.5771793083 0.9077798691 0.0795832758 1.4754487465 
##         1001         1002         1003         1004         1005 
## 0.2484286067 1.9444097270 1.0650451708 0.8801703352 1.9347138935 
##         1006         1007         1008         1009         1010 
## 1.5771793083 0.6735162668 1.9347138935 0.2583720000 0.7131671029 
##         1011         1012         1013         1014         1015 
## 0.6969654416 1.1355621816 0.7049207558 2.0390968437 0.7068483758 
##         1016         1017         1018         1019         1020 
## 0.6032426066 1.7085383790 1.1163792013 0.6488590894 0.5175996642 
##         1021         1022         1023         1024         1025 
## 0.6284486157 1.2009042576 0.8881263393 0.0003701466 0.0384032676 
##         1026         1027         1028         1029         1030 
## 0.8705469428 0.4526540489 0.6131493966 0.0799466612 1.6988783683 
##         1031         1032         1033         1034         1035 
## 0.2284857371 1.1980107186 0.6586664028 0.5293241592 0.2583720000 
##         1036         1037         1038         1039         1040 
## 1.1172375802 1.2450231264 0.5407675153 0.3417080158 1.1966984486 
##         1041         1042         1043         1044         1045 
## 0.3643258854 0.3414734522 0.1418662452 0.1638441750 2.0390968437 
##         1046         1047         1048         1049         1050 
## 0.1378317566 0.6968726978 0.6610124617 0.2819854778 0.4233096066 
##         1051         1052         1053         1054         1055 
## 0.0795832758 0.4643034726 1.3742932765 0.8705469428 1.7181767115 
##         1056         1057         1058         1059         1060 
## 0.6719450363 1.8212827943 0.5661257194 1.9152569347 0.2682855888 
##         1061         1062         1063         1064         1065 
## 0.5661257194 0.5927411794 0.2979569096 0.2979569096 1.3647097963 
##         1066         1067         1068         1069         1070 
## 0.4750504057 0.7038105911 1.0587340749 1.0171503637 0.8796165014 
##         1071         1072         1073         1074         1075 
## 0.3253876213 0.5071455466 0.0795832758 0.6208731515 0.6887739042 
##         1076         1077         1078         1079         1080 
## 0.4819815630 0.0228432922 0.4957281692 0.5785539610 1.8115946642 
##         1081         1082         1083         1084         1085 
## 1.1096812091 0.4179909726 1.2257960280 1.9444097270 1.3551049283 
##         1086         1087         1088         1089         1090 
## 0.7116903206 1.3856282201 0.7049207558 0.3418819069 0.5614028822 
##         1091         1092         1093         1094         1095 
## 0.4713708554 0.6270913980 0.5785539610 0.5929654621 0.1984323173 
##         1096         1097         1098         1099         1100 
## 1.6060788910 1.1259812244 0.6739795357 0.4429449964 0.0239371148 
##         1101         1102         1103         1104         1105 
## 2.0488454002 1.4946426569 0.6694716744 1.9347138935 1.6060788910 
##         1106         1107         1108         1109         1110 
## 1.2257960280 1.0267104204 0.4483110225 1.5771793083 0.6968726978 
##         1111         1112         1113         1114         1115 
## 1.2641653163 1.6891967734 0.5542286063 0.3738845218 0.1697733654 
##         1116         1117         1118         1119         1120 
## 0.0179174212 1.1355621816 0.6289696604 0.8267989319 0.7503168801 
##         1121         1122         1123         1124         1125 
## 1.8212827943 0.5929654621 0.2084685762 1.8018848904 0.3909457765 
##         1126         1127         1128         1129         1130 
## 0.6174239367 0.1479770934 1.6988783683 1.4658195611 1.8018848904 
##         1131         1132         1133         1134         1135 
## 2.0293265344 0.9787010837 1.4850564759 1.8212827943 2.0293265344 
##         1136         1137         1138         1139         1140 
## 0.2819854778 0.4306966893 0.4915369444 0.7629742672 0.5060104768 
##         1141         1142         1143         1144         1145 
## 0.4829042727 0.5687868370 0.4134629066 1.0267104204 0.7629742672 
##         1146         1147         1148         1149         1150 
## 0.2470052215 0.3690329880 0.6693938065 0.6835760687 1.2641653163 
##         1151         1152         1153         1154         1155 
## 0.5883013131 0.7340386349 0.6962748496 0.7049207558 1.3647097963 
##         1156         1157         1158         1159         1160 
## 0.2979569096 0.0384032676 0.6330891677 0.7068483758 0.6704493611 
##         1161         1162         1163         1164         1165 
## 0.3972178764 0.6330891677 0.4713708554 1.2450231264 1.2087197375 
##         1166         1167         1168         1169         1170 
## 0.3937118792 1.4658195611 0.7891246958 1.4946426569 0.7824941466 
##         1171         1172         1173         1174         1175 
## 0.3036559238 0.0571601798 1.6988783683 0.4527335316 0.0976052627 
##         1176         1177         1178         1179         1180 
## 1.4946426569 0.7891246958 0.7146468278 2.1441076820 0.6977586048 
##         1181         1182         1183         1184         1185 
## 0.9979673604 0.0899212938 0.0532270876 1.0267104204 0.4527335316 
##         1186         1187         1188         1189         1190 
## 0.5406597269 0.6897321560 2.1539104450 0.3643258854 0.3580990380 
##         1191         1192         1193         1194         1195 
## 0.0589587282 0.2319725688 0.4729339595 0.2384664947 0.6488590894 
##         1196         1197         1198         1199         1200 
## 0.6841371294 0.0126796547 0.1783048009 0.0126796547 0.0589587282 
##         1201         1202         1203         1204         1205 
## 0.3036559238 0.4957281692 0.4306966893 0.9979673604 0.2152912651 
##         1206         1207         1208         1209         1210 
## 0.1467836173 0.4625025234 1.3647097963 0.4483110225 0.6956989387 
##         1211         1212         1213         1214         1215 
## 1.9347138935 0.0692623989 0.6587746504 0.7243528148 0.1732348143 
##         1216         1217         1218         1219         1220 
## 0.4942142060 0.6959093482 0.2152912651 0.6544872975 0.7146468278 
##         1221         1222         1223         1224         1225 
## 0.6504882020 1.4850564759 0.8993550585 0.6191736315 0.6841371294 
##         1226         1227         1228         1229         1230 
## 0.5883013131 0.0915818254 0.1946544040 0.4246268841 0.6220719228 
##         1231         1232         1233         1234         1235 
## 1.0267104204 0.0281516095 0.8923014577 0.1966760861 1.4658195611 
##         1236         1237         1238         1239         1240 
## 0.3690329880 2.0488454002 0.0692623989 0.3527809282 0.5899560716 
##         1241 
## 0.0281516095
  • Media del error
mean(Error2)
## [1] 0.6042886
  • Desviación estándar del error
sd(Error2)
## [1] 0.4595743
  • Suma de cuadrados de los residuales
sqrt(sum(Residuales2^2)/summary(mod2)$df[2])
## [1] 0.1499655
  • AIC
AIC(mod2)
## [1] -1182.421

Modelo Logarítmico (Modelo 3)

mod3 <- lm(log(Ht)~log(DAP_cm), datos)
mod3
## 
## Call:
## lm(formula = log(Ht) ~ log(DAP_cm), data = datos)
## 
## Coefficients:
## (Intercept)  log(DAP_cm)  
##       1.353        0.540
summary(mod3)
## 
## Call:
## lm(formula = log(Ht) ~ log(DAP_cm), data = datos)
## 
## Residuals:
##        Min         1Q     Median         3Q        Max 
## -3.669e-04 -1.324e-04  1.733e-05  1.412e-04  3.216e-04 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.353e+00  3.511e-05   38548   <2e-16 ***
## log(DAP_cm) 5.400e-01  1.183e-05   45665   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.0001652 on 1239 degrees of freedom
## Multiple R-squared:      1,  Adjusted R-squared:      1 
## F-statistic: 2.085e+09 on 1 and 1239 DF,  p-value: < 2.2e-16
{par(mfrow=c(2,2))
plot(mod3)}

En este modelo solo hallamos los residulaes ya que el procesos para hallar los predichos se hace con un Factor de correción (FC) que se hace posteriormente.

  • verificamos normalidad
Residuales3 <- residuals(mod3)
shapiro.test(Residuales3)
## 
##  Shapiro-Wilk normality test
## 
## data:  Residuales3
## W = 0.97111, p-value = 4.896e-15

Para encontrar los valores predichos, usamos un factor de correcion (FC)

FC <- exp(anova(mod3)$'Mean Sq'[2]/2)
FC
## [1] 1
predichos3 <- exp(predict(mod3))*FC
  • Cálculo del error
Error3 <- abs(((predichos3-datos$Ht)/datos$Ht)*100)
Error3
##            1            2            3            4            5 
## 4.056369e-03 4.792180e-03 1.459643e-02 6.946395e-03 1.792116e-02 
##            6            7            8            9           10 
## 7.727279e-03 1.547355e-02 5.534930e-03 4.522517e-03 3.364564e-03 
##           11           12           13           14           15 
## 1.033412e-02 1.657517e-02 1.570569e-02 1.937037e-02 8.056198e-03 
##           16           17           18           19           20 
## 1.688351e-02 6.725376e-03 6.972388e-03 1.987145e-02 1.717809e-02 
##           21           22           23           24           25 
## 1.051921e-02 8.056198e-03 2.141901e-02 8.330715e-03 1.276478e-02 
##           26           27           28           29           30 
## 1.411707e-02 8.882090e-03 6.181970e-03 5.981170e-03 1.910458e-02 
##           31           32           33           34           35 
## 1.440347e-03 2.591403e-02 5.047034e-03 1.916516e-02 3.044857e-03 
##           36           37           38           39           40 
## 2.074582e-02 1.977447e-02 1.406578e-02 8.942959e-04 1.160245e-02 
##           41           42           43           44           45 
## 2.776059e-02 9.424168e-03 1.276623e-02 6.525099e-03 1.733850e-02 
##           46           47           48           49           50 
## 2.283210e-02 1.033412e-02 1.925815e-03 1.411707e-02 1.229670e-02 
##           51           52           53           54           55 
## 1.493688e-02 6.421265e-03 1.276478e-02 1.663986e-03 2.027584e-02 
##           56           57           58           59           60 
## 9.850627e-03 1.848483e-02 3.754622e-03 4.792180e-03 1.283494e-02 
##           61           62           63           64           65 
## 1.689704e-02 5.896479e-03 1.212029e-02 3.710848e-03 5.896479e-03 
##           66           67           68           69           70 
## 1.293931e-03 3.872805e-03 2.950198e-02 1.365318e-02 8.241197e-03 
##           71           72           73           74           75 
## 2.127361e-02 1.268919e-02 6.385673e-03 1.212147e-02 4.260007e-03 
##           76           77           78           79           80 
## 2.030629e-02 3.790309e-03 1.408689e-02 2.046267e-02 1.194822e-02 
##           81           82           83           84           85 
## 7.867252e-03 1.323484e-02 1.786519e-02 1.922980e-02 9.560482e-03 
##           86           87           88           89           90 
## 3.710848e-03 3.761733e-03 1.766532e-03 5.215344e-03 2.111399e-03 
##           91           92           93           94           95 
## 3.710848e-03 1.365318e-02 6.051308e-03 1.263375e-02 1.404416e-02 
##           96           97           98           99          100 
## 1.689704e-02 1.347967e-02 1.047690e-03 3.595322e-03 8.692576e-03 
##          101          102          103          104          105 
## 1.629158e-02 9.668263e-03 3.559891e-03 4.692345e-03 1.925815e-03 
##          106          107          108          109          110 
## 1.871604e-02 6.385673e-03 7.576184e-03 2.412311e-02 2.312983e-02 
##          111          112          113          114          115 
## 9.944695e-03 6.383936e-03 6.585463e-03 9.464498e-03 2.289529e-02 
##          116          117          118          119          120 
## 2.176125e-02 4.881333e-03 2.312983e-02 1.864238e-02 1.871604e-02 
##          121          122          123          124          125 
## 1.610947e-02 2.151303e-02 8.151865e-03 1.332523e-03 1.632421e-02 
##          126          127          128          129          130 
## 1.565914e-03 2.324046e-02 8.590084e-03 1.786519e-02 1.325046e-02 
##          131          132          133          134          135 
## 7.131216e-03 1.864238e-02 1.278058e-02 1.975081e-02 2.778456e-03 
##          136          137          138          139          140 
## 1.487671e-02 3.843425e-03 1.724076e-02 1.202093e-02 8.330715e-03 
##          141          142          143          144          145 
## 1.520075e-02 3.969420e-03 1.657517e-02 1.118332e-02 8.620522e-03 
##          146          147          148          149          150 
## 8.056198e-03 3.578713e-03 1.970172e-02 6.581881e-03 1.130082e-02 
##          151          152          153          154          155 
## 4.056369e-03 8.041186e-03 1.717809e-02 3.030083e-02 9.304003e-03 
##          156          157          158          159          160 
## 7.576184e-03 9.850627e-03 1.845085e-02 1.061114e-02 1.632421e-02 
##          161          162          163          164          165 
## 1.592081e-02 1.623527e-02 3.969420e-03 9.560482e-03 1.694945e-02 
##          166          167          168          169          170 
## 2.011198e-02 1.977447e-02 2.064124e-02 1.925449e-02 1.120868e-02 
##          171          172          173          174          175 
## 6.594218e-03 2.778456e-03 1.582382e-03 7.245952e-03 4.392935e-03 
##          176          177          178          179          180 
## 2.995308e-02 1.763078e-02 1.635895e-03 1.220493e-02 1.160245e-02 
##          181          182          183          184          185 
## 2.997024e-03 8.056198e-03 3.332678e-03 5.047034e-03 1.048800e-02 
##          186          187          188          189          190 
## 2.995308e-02 3.710848e-03 2.950198e-02 2.920476e-03 3.843425e-03 
##          191          192          193          194          195 
## 7.245952e-03 2.966816e-04 6.383936e-03 1.862458e-02 4.392935e-03 
##          196          197          198          199          200 
## 1.632421e-02 1.321766e-02 1.022576e-02 4.207147e-03 1.788320e-02 
##          201          202          203          204          205 
## 1.325046e-02 4.692345e-03 9.304003e-03 8.330157e-03 1.212147e-02 
##          206          207          208          209          210 
## 1.593018e-02 4.064673e-03 2.278211e-02 1.245504e-02 1.813897e-02 
##          211          212          213          214          215 
## 1.044201e-02 2.095985e-02 1.717809e-02 2.103669e-03 1.007928e-02 
##          216          217          218          219          220 
## 2.291029e-02 9.424168e-03 1.632421e-02 2.283447e-02 2.324046e-02 
##          221          222          223          224          225 
## 7.841204e-03 2.300453e-02 2.235111e-02 4.692345e-03 1.469929e-02 
##          226          227          228          229          230 
## 1.559605e-02 2.283447e-02 2.127361e-02 1.332523e-03 8.602671e-03 
##          231          232          233          234          235 
## 4.911023e-03 1.790577e-02 1.194822e-02 1.688351e-02 2.296963e-02 
##          236          237          238          239          240 
## 4.392935e-03 1.112169e-02 1.113976e-02 1.502395e-02 8.590084e-03 
##          241          242          243          244          245 
## 1.527981e-02 1.617240e-02 1.679162e-02 5.896479e-03 2.276877e-02 
##          246          247          248          249          250 
## 3.969420e-03 1.987145e-02 3.790309e-03 1.980041e-02 8.056198e-03 
##          251          252          253          254          255 
## 2.219251e-02 1.603313e-02 1.128732e-02 2.226682e-02 1.216537e-02 
##          256          257          258          259          260 
## 1.167841e-02 1.818901e-02 9.961463e-03 1.596078e-02 1.031522e-02 
##          261          262          263          264          265 
## 1.596078e-02 4.692345e-03 1.528448e-02 1.469929e-02 1.566239e-02 
##          266          267          268          269          270 
## 1.864238e-02 1.599276e-02 2.141901e-02 2.091422e-02 1.502395e-02 
##          271          272          273          274          275 
## 1.945243e-02 2.373792e-02 1.849997e-02 1.048800e-02 1.130082e-02 
##          276          277          278          279          280 
## 7.568092e-03 8.895245e-03 8.942959e-04 1.643400e-02 1.128732e-02 
##          281          282          283          284          285 
## 8.523196e-03 8.569303e-03 2.598017e-02 8.379086e-03 1.293931e-03 
##          286          287          288          289          290 
## 1.061114e-02 1.864238e-02 1.976894e-03 1.459643e-02 1.838909e-02 
##          291          292          293          294          295 
## 1.722536e-02 2.272244e-02 1.837853e-02 4.385156e-03 2.073855e-02 
##          296          297          298          299          300 
## 1.823664e-02 3.550260e-02 7.576184e-03 1.980041e-02 2.534673e-02 
##          301          302          303          304          305 
## 2.806272e-02 1.368723e-02 2.114449e-02 6.741360e-03 1.293931e-03 
##          306          307          308          309          310 
## 3.199406e-03 1.138147e-02 1.171842e-02 3.143806e-02 1.389515e-02 
##          311          312          313          314          315 
## 1.542269e-02 1.218905e-02 2.906474e-02 3.412890e-02 2.519471e-02 
##          316          317          318          319          320 
## 2.098149e-02 9.944695e-03 4.207147e-03 1.187959e-02 1.033412e-02 
##          321          322          323          324          325 
## 9.961463e-03 4.538836e-03 2.346970e-02 2.308617e-03 1.161040e-02 
##          326          327          328          329          330 
## 2.011198e-02 1.632997e-02 8.942959e-04 4.122762e-03 2.063898e-02 
##          331          332          333          334          335 
## 6.525099e-03 1.230902e-02 1.334075e-02 2.596682e-02 1.558492e-03 
##          336          337          338          339          340 
## 1.408861e-04 2.445753e-03 1.259053e-02 2.361078e-05 8.569303e-03 
##          341          342          343          344          345 
## 1.347967e-02 1.865991e-02 2.746860e-03 1.728562e-02 1.900233e-02 
##          346          347          348          349          350 
## 2.519471e-02 8.917871e-03 1.190384e-02 5.695452e-03 1.865991e-02 
##          351          352          353          354          355 
## 3.024007e-03 2.373792e-02 2.490243e-02 2.322060e-02 1.659508e-02 
##          356          357          358          359          360 
## 1.910458e-02 7.576184e-03 2.728103e-02 2.545800e-02 8.815808e-03 
##          361          362          363          364          365 
## 2.244178e-03 1.844918e-02 8.079084e-04 1.459643e-02 6.581881e-03 
##          366          367          368          369          370 
## 1.763078e-02 1.033412e-02 2.694650e-03 1.638357e-02 2.264615e-03 
##          371          372          373          374          375 
## 2.855336e-02 4.883163e-04 1.354085e-02 1.916516e-02 1.976894e-03 
##          376          377          378          379          380 
## 2.587678e-03 2.073855e-02 2.192631e-02 2.272244e-02 8.895245e-03 
##          381          382          383          384          385 
## 5.806787e-03 2.601200e-02 6.550492e-03 3.247146e-02 3.656419e-03 
##          386          387          388          389          390 
## 9.264624e-03 2.776989e-02 5.044437e-03 2.175983e-02 2.114357e-02 
##          391          392          393          394          395 
## 1.216537e-02 3.412890e-02 3.656419e-03 1.224819e-02 1.094236e-02 
##          396          397          398          399          400 
## 2.598017e-02 1.632421e-02 6.478841e-03 2.141901e-02 5.569536e-03 
##          401          402          403          404          405 
## 1.248374e-02 1.542269e-02 1.323484e-02 2.175618e-02 2.182586e-03 
##          406          407          408          409          410 
## 1.248374e-02 1.659984e-02 1.245314e-02 2.925240e-03 1.037396e-02 
##          411          412          413          414          415 
## 1.660063e-02 2.380043e-02 6.725376e-03 1.019892e-02 1.122784e-02 
##          416          417          418          419          420 
## 2.091422e-02 2.030629e-02 8.151865e-03 2.543424e-02 6.768817e-03 
##          421          422          423          424          425 
## 7.827922e-03 2.543424e-02 1.163512e-02 9.264624e-03 1.939583e-03 
##          426          427          428          429          430 
## 3.934463e-03 2.490243e-02 2.888125e-02 2.595447e-02 9.662983e-03 
##          431          432          433          434          435 
## 1.570569e-02 3.456006e-02 1.230902e-02 1.071707e-02 1.722536e-02 
##          436          437          438          439          440 
## 1.120868e-02 2.796653e-03 2.055431e-04 1.976894e-03 1.754999e-02 
##          441          442          443          444          445 
## 2.346970e-02 2.309896e-02 1.820593e-02 1.171842e-02 1.724076e-02 
##          446          447          448          449          450 
## 1.161543e-02 2.906474e-02 1.731159e-03 4.362513e-03 2.994445e-02 
##          451          452          453          454          455 
## 2.264615e-03 3.429980e-02 2.272244e-02 9.850627e-03 8.075990e-03 
##          456          457          458          459          460 
## 1.354085e-02 1.977447e-02 6.741360e-03 2.770597e-02 1.774218e-02 
##          461          462          463          464          465 
## 2.194809e-02 9.304003e-03 2.219251e-02 1.939583e-03 1.401541e-02 
##          466          467          468          469          470 
## 2.034371e-03 4.061256e-03 1.293668e-02 2.445681e-02 1.469792e-02 
##          471          472          473          474          475 
## 3.412890e-02 3.761733e-03 1.679162e-02 1.051921e-02 2.055431e-04 
##          476          477          478          479          480 
## 1.700414e-02 1.818901e-02 1.862141e-02 2.253238e-02 1.198095e-02 
##          481          482          483          484          485 
## 1.937037e-02 1.547355e-02 1.921888e-02 3.118272e-03 1.389480e-03 
##          486          487          488          489          490 
## 1.977447e-02 2.226682e-02 8.499162e-03 1.707904e-02 5.333547e-03 
##          491          492          493          494          495 
## 2.950198e-02 2.114357e-02 1.700101e-02 1.753106e-02 3.279806e-03 
##          496          497          498          499          500 
## 3.030083e-02 2.381870e-03 1.206420e-02 1.041077e-02 1.171842e-02 
##          501          502          503          504          505 
## 4.122762e-03 2.066489e-02 4.490067e-04 2.778456e-03 7.332313e-03 
##          506          507          508          509          510 
## 1.788320e-02 2.318557e-02 1.041077e-02 2.782872e-02 3.509321e-03 
##          511          512          513          514          515 
## 3.424483e-03 1.075950e-02 1.980041e-02 1.711654e-02 1.233426e-02 
##          516          517          518          519          520 
## 2.272244e-02 1.493355e-02 2.114449e-02 1.494182e-02 1.648466e-02 
##          521          522          523          524          525 
## 1.498876e-02 1.689418e-02 1.971243e-02 1.248374e-02 3.407010e-03 
##          526          527          528          529          530 
## 2.079468e-02 9.961463e-03 2.776989e-02 1.890700e-02 3.997456e-03 
##          531          532          533          534          535 
## 9.961463e-03 2.175618e-02 1.632997e-02 2.240004e-02 9.063019e-03 
##          536          537          538          539          540 
## 2.216242e-02 7.324314e-03 1.013192e-02 9.063841e-03 1.582382e-03 
##          541          542          543          544          545 
## 2.564290e-03 1.206729e-02 1.895680e-02 1.256469e-02 1.493355e-02 
##          546          547          548          549          550 
## 1.797961e-02 1.753956e-02 2.141901e-02 3.196317e-03 7.131216e-03 
##          551          552          553          554          555 
## 3.407010e-03 4.693791e-03 1.347967e-02 1.593504e-02 8.854851e-03 
##          556          557          558          559          560 
## 6.989557e-03 1.158903e-02 8.079919e-05 2.300453e-02 2.994445e-02 
##          561          562          563          564          565 
## 1.818901e-02 6.412342e-03 6.581881e-03 2.116571e-02 1.293931e-03 
##          566          567          568          569          570 
## 1.496959e-02 2.418576e-02 3.030083e-02 2.994445e-02 2.879697e-02 
##          571          572          573          574          575 
## 2.645972e-02 2.814069e-02 1.786519e-02 1.659508e-02 4.911023e-03 
##          576          577          578          579          580 
## 1.660063e-02 2.906474e-02 1.632469e-02 1.797961e-02 2.079468e-02 
##          581          582          583          584          585 
## 7.399838e-03 2.670194e-02 1.616178e-02 3.429980e-02 9.540948e-03 
##          586          587          588          589          590 
## 1.970172e-02 2.283447e-02 2.098149e-02 4.162273e-03 2.114449e-02 
##          591          592          593          594          595 
## 1.049365e-02 1.493355e-02 1.741883e-02 1.868877e-02 2.475320e-02 
##          596          597          598          599          600 
## 2.782872e-02 1.198095e-02 5.901016e-03 3.127526e-02 1.870148e-02 
##          601          602          603          604          605 
## 1.921888e-02 1.387869e-02 1.528448e-02 1.838909e-02 4.064851e-03 
##          606          607          608          609          610 
## 8.569303e-03 5.438018e-03 1.414084e-02 7.467261e-03 3.056841e-02 
##          611          612          613          614          615 
## 1.728562e-02 1.239845e-03 2.778988e-02 2.778988e-02 2.623415e-04 
##          616          617          618          619          620 
## 3.934463e-03 1.900233e-02 2.240004e-02 1.486838e-02 2.855336e-02 
##          621          622          623          624          625 
## 2.173158e-02 2.545800e-02 1.347967e-02 1.891339e-02 1.394232e-02 
##          626          627          628          629          630 
## 1.823664e-02 1.166234e-02 7.568092e-03 1.047690e-03 1.106033e-02 
##          631          632          633          634          635 
## 8.398114e-03 2.289529e-02 1.971243e-02 4.346923e-04 2.287149e-02 
##          636          637          638          639          640 
## 2.888125e-02 3.843425e-03 1.268919e-02 1.325046e-02 8.241197e-03 
##          641          642          643          644          645 
## 1.265457e-02 2.032712e-02 1.713548e-02 2.380043e-02 1.265457e-02 
##          646          647          648          649          650 
## 2.114357e-02 2.853422e-03 4.232492e-04 1.977447e-02 4.528095e-03 
##          651          652          653          654          655 
## 4.471119e-03 1.324881e-02 4.821840e-04 1.629158e-02 2.139708e-03 
##          656          657          658          659          660 
## 2.640271e-02 1.230340e-02 5.044437e-03 7.131216e-03 1.202093e-02 
##          661          662          663          664          665 
## 1.319248e-03 1.329748e-02 4.064673e-03 1.704099e-02 2.600272e-02 
##          666          667          668          669          670 
## 2.373792e-02 2.276877e-02 1.925449e-02 2.074582e-02 1.603313e-02 
##          671          672          673          674          675 
## 1.698200e-02 1.813897e-02 2.289529e-02 5.520402e-03 2.226682e-02 
##          676          677          678          679          680 
## 1.276478e-02 1.744971e-02 8.056198e-03 1.774218e-02 2.216242e-02 
##          681          682          683          684          685 
## 6.585463e-03 1.818901e-02 1.322527e-03 9.063841e-03 1.502395e-02 
##          686          687          688          689          690 
## 1.823664e-02 1.707904e-02 1.657517e-02 2.200359e-02 7.715352e-03 
##          691          692          693          694          695 
## 7.131216e-03 2.284829e-02 1.994914e-02 2.030629e-02 1.161543e-02 
##          696          697          698          699          700 
## 1.681086e-02 5.615975e-03 4.538836e-03 1.681086e-02 1.118332e-02 
##          701          702          703          704          705 
## 1.404416e-02 2.064124e-02 8.590084e-03 8.076313e-03 4.789141e-03 
##          706          707          708          709          710 
## 1.041077e-02 1.688351e-02 2.074582e-02 3.843425e-03 2.920476e-03 
##          711          712          713          714          715 
## 7.304335e-03 6.052221e-03 2.074582e-02 1.298316e-02 5.890978e-03 
##          716          717          718          719          720 
## 1.821498e-02 3.028334e-03 8.499162e-03 4.122762e-03 1.954077e-02 
##          721          722          723          724          725 
## 1.500178e-02 4.471119e-03 8.241197e-03 1.582382e-03 1.700414e-02 
##          726          727          728          729          730 
## 1.231873e-03 1.566239e-02 1.170188e-02 4.522517e-03 2.595447e-02 
##          731          732          733          734          735 
## 2.980592e-05 1.870148e-02 4.538836e-03 4.064673e-03 1.681125e-02 
##          736          737          738          739          740 
## 2.151303e-02 9.643326e-03 2.405840e-02 2.436152e-04 1.975081e-02 
##          741          742          743          744          745 
## 1.811999e-02 6.282317e-03 2.519471e-02 1.212029e-02 1.871604e-02 
##          746          747          748          749          750 
## 1.033412e-02 1.160245e-02 1.347547e-02 9.560482e-03 8.151865e-03 
##          751          752          753          754          755 
## 1.011974e-02 1.848483e-02 2.519331e-02 4.881333e-03 2.091422e-02 
##          756          757          758          759          760 
## 1.528448e-02 1.744690e-02 1.235511e-02 3.527724e-03 1.848483e-02 
##          761          762          763          764          765 
## 2.141901e-02 1.420638e-02 2.938044e-03 1.542269e-02 7.131216e-03 
##          766          767          768          769          770 
## 7.552769e-03 5.728232e-03 1.987145e-02 3.452249e-03 2.436152e-04 
##          771          772          773          774          775 
## 2.656703e-02 2.318557e-02 9.643326e-03 2.601192e-02 2.373792e-02 
##          776          777          778          779          780 
## 8.748505e-03 3.506596e-03 1.404416e-02 2.543424e-02 2.095908e-02 
##          781          782          783          784          785 
## 2.997024e-03 1.520075e-02 2.950198e-02 7.867252e-03 4.471119e-03 
##          786          787          788          789          790 
## 2.253238e-02 6.838117e-03 1.118332e-02 4.232492e-04 4.951976e-04 
##          791          792          793          794          795 
## 9.971605e-03 4.931380e-03 2.318557e-02 6.545723e-03 6.412342e-03 
##          796          797          798          799          800 
## 1.994914e-02 3.179364e-03 2.114357e-02 2.656703e-02 2.297595e-02 
##          801          802          803          804          805 
## 1.494182e-02 8.698221e-03 6.181970e-03 1.925815e-03 2.201040e-02 
##          806          807          808          809          810 
## 1.696269e-02 3.828473e-03 1.212029e-02 5.901016e-03 1.957017e-02 
##          811          812          813          814          815 
## 1.826322e-02 1.516759e-02 2.219251e-02 1.864776e-02 1.323484e-02 
##          816          817          818          819          820 
## 1.123462e-02 1.324448e-02 7.568092e-03 9.850627e-03 1.365318e-02 
##          821          822          823          824          825 
## 1.891339e-02 6.277803e-03 2.264615e-03 2.879697e-02 1.469929e-02 
##          826          827          828          829          830 
## 2.291029e-02 1.788320e-02 2.600272e-02 4.547197e-03 6.414098e-04 
##          831          832          833          834          835 
## 2.297595e-02 1.700414e-02 2.776059e-02 8.747608e-03 6.725376e-03 
##          836          837          838          839          840 
## 3.647863e-03 8.523196e-03 1.659984e-02 4.834871e-05 1.520075e-02 
##          841          842          843          844          845 
## 1.414084e-02 4.207147e-03 2.245159e-02 2.066489e-02 2.994445e-02 
##          846          847          848          849          850 
## 2.283210e-02 6.838117e-03 1.001066e-02 1.138147e-02 1.013192e-02 
##          851          852          853          854          855 
## 2.303903e-03 1.871604e-02 1.971243e-02 8.330157e-03 3.828473e-03 
##          856          857          858          859          860 
## 1.229670e-02 1.613212e-02 1.586553e-02 2.814069e-02 1.700318e-02 
##          861          862          863          864          865 
## 2.531495e-02 2.264615e-03 2.066724e-02 1.265457e-02 9.342752e-03 
##          866          867          868          869          870 
## 1.865991e-02 8.476080e-03 3.191020e-02 1.233035e-02 2.405840e-02 
##          871          872          873          874          875 
## 1.601741e-03 2.244178e-03 2.373792e-02 2.194809e-02 1.324391e-02 
##          876          877          878          879          880 
## 2.776059e-02 1.256469e-02 3.364564e-03 8.186976e-04 1.657090e-03 
##          881          882          883          884          885 
## 1.498876e-02 5.278250e-03 3.550260e-02 1.939583e-03 5.936098e-03 
##          886          887          888          889          890 
## 1.660063e-02 4.529236e-03 1.700414e-02 1.570569e-02 3.648901e-03 
##          891          892          893          894          895 
## 1.011835e-02 9.644667e-03 3.143806e-02 1.011835e-02 1.498876e-02 
##          896          897          898          899          900 
## 2.284366e-02 7.983087e-03 1.558492e-03 2.066724e-02 2.966816e-04 
##          901          902          903          904          905 
## 1.231873e-03 1.218905e-02 2.703998e-02 1.753106e-02 6.474275e-03 
##          906          907          908          909          910 
## 2.925240e-03 5.154655e-03 2.030629e-02 1.615154e-02 3.310818e-02 
##          911          912          913          914          915 
## 3.412890e-02 1.728562e-02 2.596682e-02 2.201040e-02 3.429980e-02 
##          916          917          918          919          920 
## 2.079468e-02 1.493355e-02 9.555052e-03 2.196762e-02 3.412890e-02 
##          921          922          923          924          925 
## 1.939583e-03 3.024007e-03 1.632469e-02 4.471119e-03 1.276478e-02 
##          926          927          928          929          930 
## 1.862141e-02 2.855336e-02 1.876832e-02 3.828470e-03 2.066489e-02 
##          931          932          933          934          935 
## 3.364564e-03 3.760590e-03 8.200902e-03 1.722536e-02 1.773850e-02 
##          936          937          938          939          940 
## 2.066724e-02 2.703998e-02 2.531495e-02 2.966816e-04 2.196762e-02 
##          941          942          943          944          945 
## 2.030629e-02 1.112390e-02 6.790161e-03 3.407010e-03 3.305932e-02 
##          946          947          948          949          950 
## 1.230902e-02 3.930060e-03 1.516759e-02 1.660063e-02 2.055431e-04 
##          951          952          953          954          955 
## 1.992782e-02 1.450905e-02 3.354068e-03 1.239321e-02 2.995209e-02 
##          956          957          958          959          960 
## 1.565306e-02 6.786206e-03 1.906375e-02 3.550260e-02 2.601200e-02 
##          961          962          963          964          965 
## 1.549075e-02 4.056221e-03 6.131967e-03 4.834871e-05 2.994445e-02 
##          966          967          968          969          970 
## 2.995209e-02 1.218905e-02 3.310818e-02 5.426890e-03 3.106153e-02 
##          971          972          973          974          975 
## 4.385156e-03 1.071707e-02 2.114449e-02 2.079468e-02 2.079468e-02 
##          976          977          978          979          980 
## 3.106153e-02 5.804312e-03 1.632469e-02 1.865991e-02 3.550260e-02 
##          981          982          983          984          985 
## 1.218905e-02 2.670194e-02 1.710621e-02 1.781704e-02 8.942959e-04 
##          986          987          988          989          990 
## 4.385156e-03 1.921888e-02 5.806787e-03 3.305932e-02 7.552769e-03 
##          991          992          993          994          995 
## 2.272244e-02 2.596682e-02 2.703998e-02 3.310818e-02 1.565306e-02 
##          996          997          998          999         1000 
## 1.906375e-02 3.429980e-02 4.237097e-03 1.632469e-02 1.232787e-02 
##         1001         1002         1003         1004         1005 
## 5.549862e-03 3.091092e-02 8.079084e-04 4.118884e-03 1.011835e-02 
##         1006         1007         1008         1009         1010 
## 3.429980e-02 9.850627e-03 1.011835e-02 9.662983e-03 1.263375e-02 
##         1011         1012         1013         1014         1015 
## 4.821840e-04 8.751099e-03 3.305932e-02 4.490067e-04 1.985400e-02 
##         1016         1017         1018         1019         1020 
## 8.942959e-04 2.623415e-04 1.728562e-02 4.792180e-03 2.501682e-02 
##         1021         1022         1023         1024         1025 
## 1.212147e-02 1.187484e-02 8.534679e-03 1.420638e-02 1.823651e-02 
##         1026         1027         1028         1029         1030 
## 6.478841e-03 8.241197e-03 5.838424e-03 1.411707e-02 1.862141e-02 
##         1031         1032         1033         1034         1035 
## 2.182586e-03 3.711687e-03 2.201040e-02 1.753106e-02 9.662983e-03 
##         1036         1037         1038         1039         1040 
## 5.890978e-03 6.786206e-03 1.161040e-02 3.030083e-02 9.989987e-04 
##         1041         1042         1043         1044         1045 
## 1.925449e-02 1.562686e-02 1.753956e-02 1.518853e-02 4.490067e-04 
##         1046         1047         1048         1049         1050 
## 2.906474e-02 2.127361e-02 2.776059e-02 9.643326e-03 6.131967e-03 
##         1051         1052         1053         1054         1055 
## 1.632469e-02 2.309896e-02 1.136105e-02 6.478841e-03 1.837853e-02 
##         1056         1057         1058         1059         1060 
## 2.147113e-02 3.024007e-03 1.245314e-02 3.056841e-02 1.502395e-02 
##         1061         1062         1063         1064         1065 
## 1.245314e-02 1.013192e-02 2.778988e-02 2.778988e-02 4.056221e-03 
##         1066         1067         1068         1069         1070 
## 1.469792e-02 2.429622e-02 1.370657e-03 1.498876e-02 6.857383e-03 
##         1071         1072         1073         1074         1075 
## 3.279806e-03 1.659984e-02 1.632469e-02 3.199406e-03 2.141901e-02 
##         1076         1077         1078         1079         1080 
## 3.215555e-02 2.534673e-02 1.031522e-02 1.331841e-02 1.638357e-02 
##         1081         1082         1083         1084         1085 
## 2.492765e-03 5.718732e-03 3.456006e-02 3.091092e-02 1.921888e-02 
##         1086         1087         1088         1089         1090 
## 1.870148e-02 2.391048e-03 3.305932e-02 1.033412e-02 1.985195e-02 
##         1091         1092         1093         1094         1095 
## 2.950198e-02 2.617919e-02 1.331841e-02 1.673964e-02 1.256469e-02 
##         1096         1097         1098         1099         1100 
## 1.773850e-02 4.385156e-03 2.656703e-02 5.901016e-03 6.383936e-03 
##         1101         1102         1103         1104         1105 
## 2.116571e-02 2.066724e-02 2.200359e-02 1.011835e-02 1.773850e-02 
##         1106         1107         1108         1109         1110 
## 3.456006e-02 2.728103e-02 2.156125e-02 3.429980e-02 2.127361e-02 
##         1111         1112         1113         1114         1115 
## 2.196762e-02 3.670090e-02 2.066489e-02 3.310818e-02 1.957017e-02 
##         1116         1117         1118         1119         1120 
## 2.003274e-02 8.751099e-03 1.679162e-02 1.124746e-03 7.866322e-05 
##         1121         1122         1123         1124         1125 
## 3.024007e-03 1.673964e-02 9.264624e-03 3.550260e-02 2.598017e-02 
##         1126         1127         1128         1129         1130 
## 1.788887e-02 2.670194e-02 1.862141e-02 2.843045e-02 3.550260e-02 
##         1131         1132         1133         1134         1135 
## 2.175618e-02 3.191020e-02 4.037339e-03 3.024007e-03 2.175618e-02 
##         1136         1137         1138         1139         1140 
## 9.643326e-03 7.324314e-03 1.347967e-02 2.160502e-02 9.342752e-03 
##         1141         1142         1143         1144         1145 
## 2.287149e-02 2.063898e-02 1.187959e-02 2.728103e-02 2.160502e-02 
##         1146         1147         1148         1149         1150 
## 2.994445e-02 1.797961e-02 2.600272e-02 1.582382e-03 2.196762e-02 
##         1151         1152         1153         1154         1155 
## 5.806787e-03 6.646532e-03 3.133157e-03 3.305932e-02 4.056221e-03 
##         1156         1157         1158         1159         1160 
## 2.778988e-02 1.823651e-02 6.282317e-03 1.985400e-02 2.595447e-02 
##         1161         1162         1163         1164         1165 
## 7.552769e-03 6.282317e-03 2.950198e-02 6.786206e-03 5.816141e-03 
##         1166         1167         1168         1169         1170 
## 2.284366e-02 2.843045e-02 1.527981e-02 2.066724e-02 7.747078e-03 
##         1171         1172         1173         1174         1175 
## 3.407010e-03 7.715352e-03 1.862141e-02 1.218905e-02 9.560482e-03 
##         1176         1177         1178         1179         1180 
## 2.066724e-02 1.527981e-02 2.445681e-02 8.917871e-03 3.656419e-03 
##         1181         1182         1183         1184         1185 
## 8.911278e-03 1.619103e-02 3.087163e-02 2.728103e-02 1.218905e-02 
##         1186         1187         1188         1189         1190 
## 2.091422e-02 3.364564e-03 1.354085e-02 1.925449e-02 1.414084e-02 
##         1191         1192         1193         1194         1195 
## 1.700318e-02 1.988039e-02 1.976894e-03 1.601741e-03 4.792180e-03 
##         1196         1197         1198         1199         1200 
## 1.001066e-02 2.380043e-02 1.868877e-02 2.380043e-02 1.700318e-02 
##         1201         1202         1203         1204         1205 
## 3.407010e-03 1.031522e-02 7.324314e-03 8.911278e-03 2.490243e-02 
##         1206         1207         1208         1209         1210 
## 1.845085e-02 1.865991e-02 4.056221e-03 2.156125e-02 1.977447e-02 
##         1211         1212         1213         1214         1215 
## 1.011835e-02 1.659508e-02 6.474275e-03 1.565306e-02 1.992782e-02 
##         1216         1217         1218         1219         1220 
## 6.594218e-03 9.902029e-03 2.490243e-02 2.291029e-02 2.445681e-02 
##         1221         1222         1223         1224         1225 
## 8.151865e-03 4.037339e-03 2.596682e-02 2.812393e-02 1.001066e-02 
##         1226         1227         1228         1229         1230 
## 5.806787e-03 1.093581e-02 1.406578e-02 2.412311e-02 1.365318e-02 
##         1231         1232         1233         1234         1235 
## 2.728103e-02 1.906375e-02 1.071116e-03 6.051308e-03 2.843045e-02 
##         1236         1237         1238         1239         1240 
## 1.797961e-02 2.116571e-02 1.659508e-02 2.595933e-02 4.207147e-03 
##         1241 
## 1.906375e-02
  • Media del error
mean(Error3)
## [1] 0.01410847
  • Deviación est´ndar del error
sd(Error3)
## [1] 0.008574073
  • Coeficiente de variación
sd(Error3)/mean(Error3)
## [1] 0.607725
  • Residuales
Residuales3_1 <- predichos3-datos$Ht
sqrt(sum(Residuales3_1^2)/summary(mod3)$df[2])
## [1] 0.002964127
  • AIC
AIC(mod3)
## [1] -18088.22

Conclusión

El mejor modelo es el logarítmico por lo siguiente:

  1. Realice una figura donde se represente el modelo escogido en el punto anterior.
datos$logDAP <- log(datos$DAP_cm)
ggplot(data = datos, aes(color = Bosque)) +
 geom_point(aes(x = Ht, y = logDAP)) +
 stat_smooth(method = "lm", aes(x = Ht, y = logDAP,color=Bosque))