Carga
library(wooldridge)
data(hprice1)
head(force(hprice1),n=5)
## price assess bdrms lotsize sqrft colonial lprice lassess llotsize lsqrft
## 1 300 349.1 4 6126 2438 1 5.703783 5.855359 8.720297 7.798934
## 2 370 351.5 3 9903 2076 1 5.913503 5.862210 9.200593 7.638198
## 3 191 217.7 3 5200 1374 0 5.252274 5.383118 8.556414 7.225482
## 4 195 231.8 3 4600 1448 1 5.273000 5.445875 8.433811 7.277938
## 5 373 319.1 4 6095 2514 1 5.921578 5.765504 8.715224 7.829630
Estimación
library(stargazer)
modelo_hrpice <- lm(formula = price ~ lotsize + sqrft + bdrms, data = hprice1)
stargazer(modelo_hrpice, title = "precios", type = "text", digits = 5)
##
## precios
## ===============================================
## Dependent variable:
## ---------------------------
## price
## -----------------------------------------------
## lotsize 0.00207***
## (0.00064)
##
## sqrft 0.12278***
## (0.01324)
##
## bdrms 13.85252
## (9.01015)
##
## Constant -21.77031
## (29.47504)
##
## -----------------------------------------------
## Observations 88
## R2 0.67236
## Adjusted R2 0.66066
## Residual Std. Error 59.83348 (df = 84)
## F Statistic 57.46023*** (df = 3; 84)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
Prueba JB
# Cálculo de la Prueba de Jarque-Bera
library(moments)
residuos_JB <- residuals(modelo_hrpice)
n_JB <- length(residuos_JB)
asimetria_JB <- skewness(residuos_JB)
curtosis_JB <- kurtosis(residuos_JB) - 3
JB <- n_JB/6 * (asimetria_JB^2 + 1/4*curtosis_JB^2)
print(JB)
## [1] 32.27791
# Edición de la tabla
library(dplyr)
library(gt)
library(gtExtras)
residuos_JB %>%
as_tibble() %>% # Convierte el vector residuos en una tibble (tabla) de una columna
mutate(posicion=row_number()) %>% # Agrega una columna llamada "posicion" con el número de fila
arrange(value) %>% # Ordena la tabla por los valores de residuos en orden ascendente
mutate(dist1=row_number()/n()) %>% # Agrega una columna "dist1" con los percentiles según su posición en la tabla (usando la función row_number() y n() para obtener el número de filas)
mutate(dist2=(row_number()-1)/n()) %>% # Agrega una columna "dist2" con los percentiles según su posición en la tabla, pero ajustando en una unidad para evitar problemas con los extremos de la distribución
mutate(zi=as.vector(scale(value,center=TRUE))) %>% # Agrega una columna "zi" con los valores de residuos escalados para tener media cero y varianza uno
mutate(pi=pnorm(zi,lower.tail = TRUE)) %>% # Agrega una columna "pi" con los valores de la función de distribución acumulada (CDF) de una distribución normal estándar evaluada en los valores de zi
mutate(dif1=abs(dist1-pi)) %>% # Agrega una columna "dif1" con las diferencias absolutas entre los percentiles según la posición y los valores de pi
mutate(dif2=abs(dist2-pi)) %>% # Agrega una columna "dif2" con las diferencias absolutas entre los percentiles ajustados según la posición y los valores de pi
rename(residuales=value) -> tabla_JB # Renombra la columna "value" como "residuales" y asigna la tabla resultante a la variable tabla_KS
# Formato
tabla_JB %>%
gt() %>%
tab_header("Tabla para calcular el Estadistico JB")
| Tabla para calcular el Estadistico JB |
| residuales |
posicion |
dist1 |
dist2 |
zi |
pi |
dif1 |
dif2 |
| -120.026447 |
81 |
0.01136364 |
0.00000000 |
-2.041515459 |
0.02059981 |
0.0092361731 |
0.0205998094 |
| -115.508697 |
77 |
0.02272727 |
0.01136364 |
-1.964673586 |
0.02472601 |
0.0019987418 |
0.0133623781 |
| -107.080889 |
24 |
0.03409091 |
0.02272727 |
-1.821326006 |
0.03427866 |
0.0001877487 |
0.0115513850 |
| -91.243980 |
48 |
0.04545455 |
0.03409091 |
-1.551957925 |
0.06033615 |
0.0148816002 |
0.0262452366 |
| -85.461169 |
12 |
0.05681818 |
0.04545455 |
-1.453598781 |
0.07302879 |
0.0162106057 |
0.0275742421 |
| -77.172687 |
32 |
0.06818182 |
0.05681818 |
-1.312620980 |
0.09465535 |
0.0264735301 |
0.0378371665 |
| -74.702719 |
54 |
0.07954545 |
0.06818182 |
-1.270609602 |
0.10193378 |
0.0223883300 |
0.0337519664 |
| -65.502849 |
39 |
0.09090909 |
0.07954545 |
-1.114130117 |
0.13261169 |
0.0417025941 |
0.0530662305 |
| -63.699108 |
69 |
0.10227273 |
0.09090909 |
-1.083450505 |
0.13930425 |
0.0370315271 |
0.0483951634 |
| -62.566594 |
83 |
0.11363636 |
0.10227273 |
-1.064187703 |
0.14362184 |
0.0299854747 |
0.0413491110 |
| -59.845223 |
36 |
0.12500000 |
0.11363636 |
-1.017900230 |
0.15436269 |
0.0293626861 |
0.0407263225 |
| -54.466158 |
13 |
0.13636364 |
0.12500000 |
-0.926408352 |
0.17711690 |
0.0407532663 |
0.0521169027 |
| -54.300415 |
14 |
0.14772727 |
0.13636364 |
-0.923589260 |
0.17785010 |
0.0301228311 |
0.0414864675 |
| -52.129801 |
15 |
0.15909091 |
0.14772727 |
-0.886669532 |
0.18762842 |
0.0285375141 |
0.0399011505 |
| -51.441108 |
17 |
0.17045455 |
0.15909091 |
-0.874955638 |
0.19079902 |
0.0203444766 |
0.0317081129 |
| -48.704980 |
47 |
0.18181818 |
0.17045455 |
-0.828417174 |
0.20371714 |
0.0218989601 |
0.0332625965 |
| -48.350295 |
29 |
0.19318182 |
0.18181818 |
-0.822384375 |
0.20542908 |
0.0122472664 |
0.0236109028 |
| -47.855859 |
11 |
0.20454545 |
0.19318182 |
-0.813974573 |
0.20782976 |
0.0032843043 |
0.0146479407 |
| -45.639765 |
1 |
0.21590909 |
0.20454545 |
-0.776281294 |
0.21879146 |
0.0028823668 |
0.0142460032 |
| -43.142550 |
9 |
0.22727273 |
0.21590909 |
-0.733806463 |
0.23153335 |
0.0042606233 |
0.0156242596 |
| -41.749618 |
57 |
0.23863636 |
0.22727273 |
-0.710114247 |
0.23881665 |
0.0001802823 |
0.0115439187 |
| -40.869022 |
27 |
0.25000000 |
0.23863636 |
-0.695136302 |
0.24348494 |
0.0065150566 |
0.0048485798 |
| -37.749811 |
34 |
0.26136364 |
0.25000000 |
-0.642082009 |
0.26040997 |
0.0009536682 |
0.0104099682 |
| -36.663785 |
71 |
0.27272727 |
0.26136364 |
-0.623609925 |
0.26644190 |
0.0062853771 |
0.0050782592 |
| -36.646568 |
79 |
0.28409091 |
0.27272727 |
-0.623317083 |
0.26653809 |
0.0175528221 |
0.0061891857 |
| -33.801248 |
37 |
0.29545455 |
0.28409091 |
-0.574921384 |
0.28267223 |
0.0127823120 |
0.0014186757 |
| -29.766931 |
16 |
0.30681818 |
0.29545455 |
-0.506302171 |
0.30632227 |
0.0004959124 |
0.0108677240 |
| -26.696234 |
22 |
0.31818182 |
0.30681818 |
-0.454073044 |
0.32488813 |
0.0067063089 |
0.0180699452 |
| -24.271531 |
23 |
0.32954545 |
0.31818182 |
-0.412831567 |
0.33986501 |
0.0103195566 |
0.0216831929 |
| -23.651448 |
86 |
0.34090909 |
0.32954545 |
-0.402284648 |
0.34373728 |
0.0028281851 |
0.0141918214 |
| -19.683427 |
88 |
0.35227273 |
0.34090909 |
-0.334793052 |
0.36889060 |
0.0166178738 |
0.0279815102 |
| -17.817835 |
10 |
0.36363636 |
0.35227273 |
-0.303061413 |
0.38092153 |
0.0172851663 |
0.0286488027 |
| -16.762094 |
60 |
0.37500000 |
0.36363636 |
-0.285104441 |
0.38778206 |
0.0127820638 |
0.0241457002 |
| -16.596960 |
21 |
0.38636364 |
0.37500000 |
-0.282295711 |
0.38885839 |
0.0024947507 |
0.0138583870 |
| -16.271207 |
58 |
0.39772727 |
0.38636364 |
-0.276755010 |
0.39098411 |
0.0067431583 |
0.0046204781 |
| -13.815798 |
56 |
0.40909091 |
0.39772727 |
-0.234991254 |
0.40710776 |
0.0019831485 |
0.0093804879 |
| -13.462160 |
75 |
0.42045455 |
0.40909091 |
-0.228976273 |
0.40944368 |
0.0110108666 |
0.0003527698 |
| -12.081520 |
4 |
0.43181818 |
0.42045455 |
-0.205493119 |
0.41859344 |
0.0132247451 |
0.0018611087 |
| -11.629207 |
51 |
0.44318182 |
0.43181818 |
-0.197799788 |
0.42160086 |
0.0215809622 |
0.0102173258 |
| -11.312669 |
74 |
0.45454545 |
0.44318182 |
-0.192415834 |
0.42370825 |
0.0308372092 |
0.0194735728 |
| -8.236558 |
3 |
0.46590909 |
0.45454545 |
-0.140094626 |
0.44429261 |
0.0216164775 |
0.0102528411 |
| -7.662789 |
70 |
0.47727273 |
0.46590909 |
-0.130335452 |
0.44815052 |
0.0291222111 |
0.0177585748 |
| -6.752801 |
67 |
0.48863636 |
0.47727273 |
-0.114857588 |
0.45427900 |
0.0343573625 |
0.0229937262 |
| -6.707262 |
31 |
0.50000000 |
0.48863636 |
-0.114083016 |
0.45458599 |
0.0454140074 |
0.0340503710 |
| -6.402439 |
85 |
0.51136364 |
0.50000000 |
-0.108898313 |
0.45664157 |
0.0547220642 |
0.0433584278 |
| -5.446904 |
82 |
0.52272727 |
0.51136364 |
-0.092645733 |
0.46309251 |
0.0596347676 |
0.0482711313 |
| -3.537785 |
43 |
0.53409091 |
0.52272727 |
-0.060173762 |
0.47600862 |
0.0580822876 |
0.0467186512 |
| -2.824941 |
61 |
0.54545455 |
0.53409091 |
-0.048049090 |
0.48083856 |
0.0646159857 |
0.0532523493 |
| -2.745208 |
68 |
0.55681818 |
0.54545455 |
-0.046692922 |
0.48137899 |
0.0754391961 |
0.0640755598 |
| -0.195089 |
65 |
0.56818182 |
0.55681818 |
-0.003318245 |
0.49867621 |
0.0695056040 |
0.0581419676 |
| 1.399296 |
55 |
0.57954545 |
0.56818182 |
0.023800450 |
0.50949411 |
0.0700513452 |
0.0586877088 |
| 5.363331 |
26 |
0.59090909 |
0.57954545 |
0.091224254 |
0.53634280 |
0.0545662924 |
0.0432026561 |
| 6.700640 |
53 |
0.60227273 |
0.59090909 |
0.113970383 |
0.54536936 |
0.0569033628 |
0.0455397265 |
| 7.386314 |
80 |
0.61363636 |
0.60227273 |
0.125632935 |
0.54998875 |
0.0636476093 |
0.0522839730 |
| 9.099900 |
41 |
0.62500000 |
0.61363636 |
0.154779103 |
0.56150227 |
0.0634977329 |
0.0521340965 |
| 12.433611 |
46 |
0.63636364 |
0.62500000 |
0.211481796 |
0.58374433 |
0.0526193043 |
0.0412556680 |
| 16.718018 |
62 |
0.64772727 |
0.63636364 |
0.284354766 |
0.61193074 |
0.0357965328 |
0.0244328965 |
| 18.093192 |
5 |
0.65909091 |
0.64772727 |
0.307744934 |
0.62086179 |
0.0382291219 |
0.0268654856 |
| 18.801816 |
38 |
0.67045455 |
0.65909091 |
0.319797835 |
0.62543921 |
0.0450153400 |
0.0336517036 |
| 19.168108 |
33 |
0.68181818 |
0.67045455 |
0.326028052 |
0.62779843 |
0.0540197476 |
0.0426561112 |
| 19.219211 |
72 |
0.69318182 |
0.68181818 |
0.326897255 |
0.62812720 |
0.0650546167 |
0.0536909803 |
| 20.334434 |
59 |
0.70454545 |
0.69318182 |
0.345865960 |
0.63527827 |
0.0692671805 |
0.0579035442 |
| 24.909926 |
78 |
0.71590909 |
0.70454545 |
0.423689939 |
0.66410402 |
0.0518050676 |
0.0404414312 |
| 26.236229 |
40 |
0.72727273 |
0.71590909 |
0.446248874 |
0.67229126 |
0.0549814685 |
0.0436178321 |
| 30.924022 |
25 |
0.73863636 |
0.72727273 |
0.525982978 |
0.70054998 |
0.0380863808 |
0.0267227444 |
| 32.253952 |
45 |
0.75000000 |
0.73863636 |
0.548603608 |
0.70836125 |
0.0416387548 |
0.0302751184 |
| 32.529367 |
49 |
0.76136364 |
0.75000000 |
0.553288104 |
0.70996693 |
0.0513967091 |
0.0400330727 |
| 32.675968 |
18 |
0.77272727 |
0.76136364 |
0.555781630 |
0.71081993 |
0.0619073452 |
0.0505437088 |
| 33.275839 |
20 |
0.78409091 |
0.77272727 |
0.565984762 |
0.71429793 |
0.0697929786 |
0.0584293423 |
| 36.031430 |
52 |
0.79545455 |
0.78409091 |
0.612854281 |
0.73001365 |
0.0654408934 |
0.0540772571 |
| 37.147186 |
84 |
0.80681818 |
0.79545455 |
0.631832029 |
0.73625168 |
0.0705665028 |
0.0592028664 |
| 40.320875 |
7 |
0.81818182 |
0.80681818 |
0.685812928 |
0.75358446 |
0.0645973596 |
0.0532337232 |
| 44.334467 |
30 |
0.82954545 |
0.81818182 |
0.754079634 |
0.77459930 |
0.0549461574 |
0.0435825211 |
| 46.907165 |
28 |
0.84090909 |
0.82954545 |
0.797838357 |
0.78751785 |
0.0533912405 |
0.0420276041 |
| 54.418366 |
87 |
0.85227273 |
0.84090909 |
0.925595465 |
0.82267187 |
0.0296008528 |
0.0182372164 |
| 55.091131 |
35 |
0.86363636 |
0.85227273 |
0.937038450 |
0.82563061 |
0.0380057535 |
0.0266421172 |
| 55.470305 |
44 |
0.87500000 |
0.86363636 |
0.943487765 |
0.82728426 |
0.0477157353 |
0.0363520989 |
| 62.939597 |
6 |
0.88636364 |
0.87500000 |
1.070532059 |
0.85781006 |
0.0285535797 |
0.0171899433 |
| 66.478628 |
50 |
0.89772727 |
0.88636364 |
1.130727018 |
0.87091500 |
0.0268122757 |
0.0154486394 |
| 67.426518 |
63 |
0.90909091 |
0.89772727 |
1.146849569 |
0.87427810 |
0.0348128083 |
0.0234491719 |
| 67.603959 |
19 |
0.92045455 |
0.90909091 |
1.149867648 |
0.87490081 |
0.0455537393 |
0.0341901029 |
| 69.707122 |
64 |
0.93181818 |
0.92045455 |
1.185640095 |
0.88211777 |
0.0497004123 |
0.0383367759 |
| 69.843246 |
8 |
0.94318182 |
0.93181818 |
1.187955411 |
0.88257451 |
0.0606073068 |
0.0492436705 |
| 74.848732 |
2 |
0.95454545 |
0.94318182 |
1.273093116 |
0.89850750 |
0.0560379553 |
0.0446743189 |
| 112.729191 |
66 |
0.96590909 |
0.95454545 |
1.917397313 |
0.97240626 |
0.0064971714 |
0.0178608078 |
| 163.795081 |
73 |
0.97727273 |
0.96590909 |
2.785970904 |
0.99733162 |
0.0200588896 |
0.0314225260 |
| 198.660139 |
42 |
0.98863636 |
0.97727273 |
3.378986513 |
0.99963623 |
0.0109998685 |
0.0223635048 |
| 209.375830 |
76 |
1.00000000 |
0.98863636 |
3.561248407 |
0.99981545 |
0.0001845478 |
0.0111790885 |
Prueba JB Gráfico
library(fastGraph)
# Calcula los residuos estandarizados
residuos_JB_graph <- scale(modelo_hrpice$residuals)
# Gráfico de la distribución de los residuos
hist(residuos_JB_graph, freq = FALSE, main = "Distribucion de los residuos estandarizados", xlab = "Residuos estandarizados")
# Añade una curva de la distribución normal para comparar
curve(dnorm(x, mean=mean(residuos_JB_graph), sd=sd(residuos_JB_graph)), add=TRUE, col="blue", lwd=2)
Prueba KS
residuos_KS <- residuals(modelo_hrpice) # Crea un vector con los residuos del modelo
n_KS <- length(residuos_KS) # Obtiene el número de observaciones
residuos_ordenados_KS <- sort(residuos_KS) # Ordena los residuos
d_plus <- max((1:n_KS)/n_KS - pnorm(residuos_ordenados_KS)) # Calcula D+
d_minus <- max(pnorm(residuos_ordenados_KS) - (0:(n_KS-1))/n_KS) # Calcula D-
D_KS <- max(d_plus, d_minus) # Calcula D
print(D_KS)
## [1] 0.5537946
# Edición de la tabla
library(dplyr)
library(gt)
library(gtExtras)
residuos_KS %>%
as_tibble() %>%
mutate(posicion=row_number()) %>%
arrange(value) %>%
mutate(dist1=row_number()/n()) %>%
mutate(dist2=(row_number()-1)/n()) %>%
mutate(zi=as.vector(scale(value,center=TRUE))) %>%
mutate(pi=pnorm(zi,lower.tail = TRUE)) %>%
mutate(dif1=abs(dist1-pi)) %>%
mutate(dif2=abs(dist2-pi)) %>%
rename(residuales=value) -> tabla_KS
# Formato
tabla_KS %>%
gt() %>%
tab_header("Tabla para calcular el Estadistico KS")
| Tabla para calcular el Estadistico KS |
| residuales |
posicion |
dist1 |
dist2 |
zi |
pi |
dif1 |
dif2 |
| -120.026447 |
81 |
0.01136364 |
0.00000000 |
-2.041515459 |
0.02059981 |
0.0092361731 |
0.0205998094 |
| -115.508697 |
77 |
0.02272727 |
0.01136364 |
-1.964673586 |
0.02472601 |
0.0019987418 |
0.0133623781 |
| -107.080889 |
24 |
0.03409091 |
0.02272727 |
-1.821326006 |
0.03427866 |
0.0001877487 |
0.0115513850 |
| -91.243980 |
48 |
0.04545455 |
0.03409091 |
-1.551957925 |
0.06033615 |
0.0148816002 |
0.0262452366 |
| -85.461169 |
12 |
0.05681818 |
0.04545455 |
-1.453598781 |
0.07302879 |
0.0162106057 |
0.0275742421 |
| -77.172687 |
32 |
0.06818182 |
0.05681818 |
-1.312620980 |
0.09465535 |
0.0264735301 |
0.0378371665 |
| -74.702719 |
54 |
0.07954545 |
0.06818182 |
-1.270609602 |
0.10193378 |
0.0223883300 |
0.0337519664 |
| -65.502849 |
39 |
0.09090909 |
0.07954545 |
-1.114130117 |
0.13261169 |
0.0417025941 |
0.0530662305 |
| -63.699108 |
69 |
0.10227273 |
0.09090909 |
-1.083450505 |
0.13930425 |
0.0370315271 |
0.0483951634 |
| -62.566594 |
83 |
0.11363636 |
0.10227273 |
-1.064187703 |
0.14362184 |
0.0299854747 |
0.0413491110 |
| -59.845223 |
36 |
0.12500000 |
0.11363636 |
-1.017900230 |
0.15436269 |
0.0293626861 |
0.0407263225 |
| -54.466158 |
13 |
0.13636364 |
0.12500000 |
-0.926408352 |
0.17711690 |
0.0407532663 |
0.0521169027 |
| -54.300415 |
14 |
0.14772727 |
0.13636364 |
-0.923589260 |
0.17785010 |
0.0301228311 |
0.0414864675 |
| -52.129801 |
15 |
0.15909091 |
0.14772727 |
-0.886669532 |
0.18762842 |
0.0285375141 |
0.0399011505 |
| -51.441108 |
17 |
0.17045455 |
0.15909091 |
-0.874955638 |
0.19079902 |
0.0203444766 |
0.0317081129 |
| -48.704980 |
47 |
0.18181818 |
0.17045455 |
-0.828417174 |
0.20371714 |
0.0218989601 |
0.0332625965 |
| -48.350295 |
29 |
0.19318182 |
0.18181818 |
-0.822384375 |
0.20542908 |
0.0122472664 |
0.0236109028 |
| -47.855859 |
11 |
0.20454545 |
0.19318182 |
-0.813974573 |
0.20782976 |
0.0032843043 |
0.0146479407 |
| -45.639765 |
1 |
0.21590909 |
0.20454545 |
-0.776281294 |
0.21879146 |
0.0028823668 |
0.0142460032 |
| -43.142550 |
9 |
0.22727273 |
0.21590909 |
-0.733806463 |
0.23153335 |
0.0042606233 |
0.0156242596 |
| -41.749618 |
57 |
0.23863636 |
0.22727273 |
-0.710114247 |
0.23881665 |
0.0001802823 |
0.0115439187 |
| -40.869022 |
27 |
0.25000000 |
0.23863636 |
-0.695136302 |
0.24348494 |
0.0065150566 |
0.0048485798 |
| -37.749811 |
34 |
0.26136364 |
0.25000000 |
-0.642082009 |
0.26040997 |
0.0009536682 |
0.0104099682 |
| -36.663785 |
71 |
0.27272727 |
0.26136364 |
-0.623609925 |
0.26644190 |
0.0062853771 |
0.0050782592 |
| -36.646568 |
79 |
0.28409091 |
0.27272727 |
-0.623317083 |
0.26653809 |
0.0175528221 |
0.0061891857 |
| -33.801248 |
37 |
0.29545455 |
0.28409091 |
-0.574921384 |
0.28267223 |
0.0127823120 |
0.0014186757 |
| -29.766931 |
16 |
0.30681818 |
0.29545455 |
-0.506302171 |
0.30632227 |
0.0004959124 |
0.0108677240 |
| -26.696234 |
22 |
0.31818182 |
0.30681818 |
-0.454073044 |
0.32488813 |
0.0067063089 |
0.0180699452 |
| -24.271531 |
23 |
0.32954545 |
0.31818182 |
-0.412831567 |
0.33986501 |
0.0103195566 |
0.0216831929 |
| -23.651448 |
86 |
0.34090909 |
0.32954545 |
-0.402284648 |
0.34373728 |
0.0028281851 |
0.0141918214 |
| -19.683427 |
88 |
0.35227273 |
0.34090909 |
-0.334793052 |
0.36889060 |
0.0166178738 |
0.0279815102 |
| -17.817835 |
10 |
0.36363636 |
0.35227273 |
-0.303061413 |
0.38092153 |
0.0172851663 |
0.0286488027 |
| -16.762094 |
60 |
0.37500000 |
0.36363636 |
-0.285104441 |
0.38778206 |
0.0127820638 |
0.0241457002 |
| -16.596960 |
21 |
0.38636364 |
0.37500000 |
-0.282295711 |
0.38885839 |
0.0024947507 |
0.0138583870 |
| -16.271207 |
58 |
0.39772727 |
0.38636364 |
-0.276755010 |
0.39098411 |
0.0067431583 |
0.0046204781 |
| -13.815798 |
56 |
0.40909091 |
0.39772727 |
-0.234991254 |
0.40710776 |
0.0019831485 |
0.0093804879 |
| -13.462160 |
75 |
0.42045455 |
0.40909091 |
-0.228976273 |
0.40944368 |
0.0110108666 |
0.0003527698 |
| -12.081520 |
4 |
0.43181818 |
0.42045455 |
-0.205493119 |
0.41859344 |
0.0132247451 |
0.0018611087 |
| -11.629207 |
51 |
0.44318182 |
0.43181818 |
-0.197799788 |
0.42160086 |
0.0215809622 |
0.0102173258 |
| -11.312669 |
74 |
0.45454545 |
0.44318182 |
-0.192415834 |
0.42370825 |
0.0308372092 |
0.0194735728 |
| -8.236558 |
3 |
0.46590909 |
0.45454545 |
-0.140094626 |
0.44429261 |
0.0216164775 |
0.0102528411 |
| -7.662789 |
70 |
0.47727273 |
0.46590909 |
-0.130335452 |
0.44815052 |
0.0291222111 |
0.0177585748 |
| -6.752801 |
67 |
0.48863636 |
0.47727273 |
-0.114857588 |
0.45427900 |
0.0343573625 |
0.0229937262 |
| -6.707262 |
31 |
0.50000000 |
0.48863636 |
-0.114083016 |
0.45458599 |
0.0454140074 |
0.0340503710 |
| -6.402439 |
85 |
0.51136364 |
0.50000000 |
-0.108898313 |
0.45664157 |
0.0547220642 |
0.0433584278 |
| -5.446904 |
82 |
0.52272727 |
0.51136364 |
-0.092645733 |
0.46309251 |
0.0596347676 |
0.0482711313 |
| -3.537785 |
43 |
0.53409091 |
0.52272727 |
-0.060173762 |
0.47600862 |
0.0580822876 |
0.0467186512 |
| -2.824941 |
61 |
0.54545455 |
0.53409091 |
-0.048049090 |
0.48083856 |
0.0646159857 |
0.0532523493 |
| -2.745208 |
68 |
0.55681818 |
0.54545455 |
-0.046692922 |
0.48137899 |
0.0754391961 |
0.0640755598 |
| -0.195089 |
65 |
0.56818182 |
0.55681818 |
-0.003318245 |
0.49867621 |
0.0695056040 |
0.0581419676 |
| 1.399296 |
55 |
0.57954545 |
0.56818182 |
0.023800450 |
0.50949411 |
0.0700513452 |
0.0586877088 |
| 5.363331 |
26 |
0.59090909 |
0.57954545 |
0.091224254 |
0.53634280 |
0.0545662924 |
0.0432026561 |
| 6.700640 |
53 |
0.60227273 |
0.59090909 |
0.113970383 |
0.54536936 |
0.0569033628 |
0.0455397265 |
| 7.386314 |
80 |
0.61363636 |
0.60227273 |
0.125632935 |
0.54998875 |
0.0636476093 |
0.0522839730 |
| 9.099900 |
41 |
0.62500000 |
0.61363636 |
0.154779103 |
0.56150227 |
0.0634977329 |
0.0521340965 |
| 12.433611 |
46 |
0.63636364 |
0.62500000 |
0.211481796 |
0.58374433 |
0.0526193043 |
0.0412556680 |
| 16.718018 |
62 |
0.64772727 |
0.63636364 |
0.284354766 |
0.61193074 |
0.0357965328 |
0.0244328965 |
| 18.093192 |
5 |
0.65909091 |
0.64772727 |
0.307744934 |
0.62086179 |
0.0382291219 |
0.0268654856 |
| 18.801816 |
38 |
0.67045455 |
0.65909091 |
0.319797835 |
0.62543921 |
0.0450153400 |
0.0336517036 |
| 19.168108 |
33 |
0.68181818 |
0.67045455 |
0.326028052 |
0.62779843 |
0.0540197476 |
0.0426561112 |
| 19.219211 |
72 |
0.69318182 |
0.68181818 |
0.326897255 |
0.62812720 |
0.0650546167 |
0.0536909803 |
| 20.334434 |
59 |
0.70454545 |
0.69318182 |
0.345865960 |
0.63527827 |
0.0692671805 |
0.0579035442 |
| 24.909926 |
78 |
0.71590909 |
0.70454545 |
0.423689939 |
0.66410402 |
0.0518050676 |
0.0404414312 |
| 26.236229 |
40 |
0.72727273 |
0.71590909 |
0.446248874 |
0.67229126 |
0.0549814685 |
0.0436178321 |
| 30.924022 |
25 |
0.73863636 |
0.72727273 |
0.525982978 |
0.70054998 |
0.0380863808 |
0.0267227444 |
| 32.253952 |
45 |
0.75000000 |
0.73863636 |
0.548603608 |
0.70836125 |
0.0416387548 |
0.0302751184 |
| 32.529367 |
49 |
0.76136364 |
0.75000000 |
0.553288104 |
0.70996693 |
0.0513967091 |
0.0400330727 |
| 32.675968 |
18 |
0.77272727 |
0.76136364 |
0.555781630 |
0.71081993 |
0.0619073452 |
0.0505437088 |
| 33.275839 |
20 |
0.78409091 |
0.77272727 |
0.565984762 |
0.71429793 |
0.0697929786 |
0.0584293423 |
| 36.031430 |
52 |
0.79545455 |
0.78409091 |
0.612854281 |
0.73001365 |
0.0654408934 |
0.0540772571 |
| 37.147186 |
84 |
0.80681818 |
0.79545455 |
0.631832029 |
0.73625168 |
0.0705665028 |
0.0592028664 |
| 40.320875 |
7 |
0.81818182 |
0.80681818 |
0.685812928 |
0.75358446 |
0.0645973596 |
0.0532337232 |
| 44.334467 |
30 |
0.82954545 |
0.81818182 |
0.754079634 |
0.77459930 |
0.0549461574 |
0.0435825211 |
| 46.907165 |
28 |
0.84090909 |
0.82954545 |
0.797838357 |
0.78751785 |
0.0533912405 |
0.0420276041 |
| 54.418366 |
87 |
0.85227273 |
0.84090909 |
0.925595465 |
0.82267187 |
0.0296008528 |
0.0182372164 |
| 55.091131 |
35 |
0.86363636 |
0.85227273 |
0.937038450 |
0.82563061 |
0.0380057535 |
0.0266421172 |
| 55.470305 |
44 |
0.87500000 |
0.86363636 |
0.943487765 |
0.82728426 |
0.0477157353 |
0.0363520989 |
| 62.939597 |
6 |
0.88636364 |
0.87500000 |
1.070532059 |
0.85781006 |
0.0285535797 |
0.0171899433 |
| 66.478628 |
50 |
0.89772727 |
0.88636364 |
1.130727018 |
0.87091500 |
0.0268122757 |
0.0154486394 |
| 67.426518 |
63 |
0.90909091 |
0.89772727 |
1.146849569 |
0.87427810 |
0.0348128083 |
0.0234491719 |
| 67.603959 |
19 |
0.92045455 |
0.90909091 |
1.149867648 |
0.87490081 |
0.0455537393 |
0.0341901029 |
| 69.707122 |
64 |
0.93181818 |
0.92045455 |
1.185640095 |
0.88211777 |
0.0497004123 |
0.0383367759 |
| 69.843246 |
8 |
0.94318182 |
0.93181818 |
1.187955411 |
0.88257451 |
0.0606073068 |
0.0492436705 |
| 74.848732 |
2 |
0.95454545 |
0.94318182 |
1.273093116 |
0.89850750 |
0.0560379553 |
0.0446743189 |
| 112.729191 |
66 |
0.96590909 |
0.95454545 |
1.917397313 |
0.97240626 |
0.0064971714 |
0.0178608078 |
| 163.795081 |
73 |
0.97727273 |
0.96590909 |
2.785970904 |
0.99733162 |
0.0200588896 |
0.0314225260 |
| 198.660139 |
42 |
0.98863636 |
0.97727273 |
3.378986513 |
0.99963623 |
0.0109998685 |
0.0223635048 |
| 209.375830 |
76 |
1.00000000 |
0.98863636 |
3.561248407 |
0.99981545 |
0.0001845478 |
0.0111790885 |
Prueba SW
# Cálculo de la Prueba de Shapiro-Wilk
residuos_SW <- residuals(modelo_hrpice) # Crea un vector con los residuos del modelo
n_SW <- length(residuos_SW) # Obtiene el número de observaciones
SW <- shapiro.test(residuos_SW)$statistic # Calcula el estadístico W de la prueba de Shapiro-Wilk
print(SW)
## W
## 0.9413208
# Edición de la tabla
library(dplyr)
library(gt)
library(gtExtras)
residuos_SW %>%
as_tibble() %>%
mutate(posicion=row_number()) %>%
arrange(value) %>%
mutate(dist1=row_number()/n()) %>%
mutate(dist2=(row_number()-1)/n()) %>%
mutate(zi=as.vector(scale(value,center=TRUE))) %>%
mutate(pi=pnorm(zi,lower.tail = TRUE)) %>%
mutate(dif1=abs(dist1-pi)) %>%
mutate(dif2=abs(dist2-pi)) %>%
rename(residuales=value) -> tabla_SW
# Formato
tabla_SW %>%
gt() %>%
tab_header("Tabla para calcular el Estadistico SW")
| Tabla para calcular el Estadistico SW |
| residuales |
posicion |
dist1 |
dist2 |
zi |
pi |
dif1 |
dif2 |
| -120.026447 |
81 |
0.01136364 |
0.00000000 |
-2.041515459 |
0.02059981 |
0.0092361731 |
0.0205998094 |
| -115.508697 |
77 |
0.02272727 |
0.01136364 |
-1.964673586 |
0.02472601 |
0.0019987418 |
0.0133623781 |
| -107.080889 |
24 |
0.03409091 |
0.02272727 |
-1.821326006 |
0.03427866 |
0.0001877487 |
0.0115513850 |
| -91.243980 |
48 |
0.04545455 |
0.03409091 |
-1.551957925 |
0.06033615 |
0.0148816002 |
0.0262452366 |
| -85.461169 |
12 |
0.05681818 |
0.04545455 |
-1.453598781 |
0.07302879 |
0.0162106057 |
0.0275742421 |
| -77.172687 |
32 |
0.06818182 |
0.05681818 |
-1.312620980 |
0.09465535 |
0.0264735301 |
0.0378371665 |
| -74.702719 |
54 |
0.07954545 |
0.06818182 |
-1.270609602 |
0.10193378 |
0.0223883300 |
0.0337519664 |
| -65.502849 |
39 |
0.09090909 |
0.07954545 |
-1.114130117 |
0.13261169 |
0.0417025941 |
0.0530662305 |
| -63.699108 |
69 |
0.10227273 |
0.09090909 |
-1.083450505 |
0.13930425 |
0.0370315271 |
0.0483951634 |
| -62.566594 |
83 |
0.11363636 |
0.10227273 |
-1.064187703 |
0.14362184 |
0.0299854747 |
0.0413491110 |
| -59.845223 |
36 |
0.12500000 |
0.11363636 |
-1.017900230 |
0.15436269 |
0.0293626861 |
0.0407263225 |
| -54.466158 |
13 |
0.13636364 |
0.12500000 |
-0.926408352 |
0.17711690 |
0.0407532663 |
0.0521169027 |
| -54.300415 |
14 |
0.14772727 |
0.13636364 |
-0.923589260 |
0.17785010 |
0.0301228311 |
0.0414864675 |
| -52.129801 |
15 |
0.15909091 |
0.14772727 |
-0.886669532 |
0.18762842 |
0.0285375141 |
0.0399011505 |
| -51.441108 |
17 |
0.17045455 |
0.15909091 |
-0.874955638 |
0.19079902 |
0.0203444766 |
0.0317081129 |
| -48.704980 |
47 |
0.18181818 |
0.17045455 |
-0.828417174 |
0.20371714 |
0.0218989601 |
0.0332625965 |
| -48.350295 |
29 |
0.19318182 |
0.18181818 |
-0.822384375 |
0.20542908 |
0.0122472664 |
0.0236109028 |
| -47.855859 |
11 |
0.20454545 |
0.19318182 |
-0.813974573 |
0.20782976 |
0.0032843043 |
0.0146479407 |
| -45.639765 |
1 |
0.21590909 |
0.20454545 |
-0.776281294 |
0.21879146 |
0.0028823668 |
0.0142460032 |
| -43.142550 |
9 |
0.22727273 |
0.21590909 |
-0.733806463 |
0.23153335 |
0.0042606233 |
0.0156242596 |
| -41.749618 |
57 |
0.23863636 |
0.22727273 |
-0.710114247 |
0.23881665 |
0.0001802823 |
0.0115439187 |
| -40.869022 |
27 |
0.25000000 |
0.23863636 |
-0.695136302 |
0.24348494 |
0.0065150566 |
0.0048485798 |
| -37.749811 |
34 |
0.26136364 |
0.25000000 |
-0.642082009 |
0.26040997 |
0.0009536682 |
0.0104099682 |
| -36.663785 |
71 |
0.27272727 |
0.26136364 |
-0.623609925 |
0.26644190 |
0.0062853771 |
0.0050782592 |
| -36.646568 |
79 |
0.28409091 |
0.27272727 |
-0.623317083 |
0.26653809 |
0.0175528221 |
0.0061891857 |
| -33.801248 |
37 |
0.29545455 |
0.28409091 |
-0.574921384 |
0.28267223 |
0.0127823120 |
0.0014186757 |
| -29.766931 |
16 |
0.30681818 |
0.29545455 |
-0.506302171 |
0.30632227 |
0.0004959124 |
0.0108677240 |
| -26.696234 |
22 |
0.31818182 |
0.30681818 |
-0.454073044 |
0.32488813 |
0.0067063089 |
0.0180699452 |
| -24.271531 |
23 |
0.32954545 |
0.31818182 |
-0.412831567 |
0.33986501 |
0.0103195566 |
0.0216831929 |
| -23.651448 |
86 |
0.34090909 |
0.32954545 |
-0.402284648 |
0.34373728 |
0.0028281851 |
0.0141918214 |
| -19.683427 |
88 |
0.35227273 |
0.34090909 |
-0.334793052 |
0.36889060 |
0.0166178738 |
0.0279815102 |
| -17.817835 |
10 |
0.36363636 |
0.35227273 |
-0.303061413 |
0.38092153 |
0.0172851663 |
0.0286488027 |
| -16.762094 |
60 |
0.37500000 |
0.36363636 |
-0.285104441 |
0.38778206 |
0.0127820638 |
0.0241457002 |
| -16.596960 |
21 |
0.38636364 |
0.37500000 |
-0.282295711 |
0.38885839 |
0.0024947507 |
0.0138583870 |
| -16.271207 |
58 |
0.39772727 |
0.38636364 |
-0.276755010 |
0.39098411 |
0.0067431583 |
0.0046204781 |
| -13.815798 |
56 |
0.40909091 |
0.39772727 |
-0.234991254 |
0.40710776 |
0.0019831485 |
0.0093804879 |
| -13.462160 |
75 |
0.42045455 |
0.40909091 |
-0.228976273 |
0.40944368 |
0.0110108666 |
0.0003527698 |
| -12.081520 |
4 |
0.43181818 |
0.42045455 |
-0.205493119 |
0.41859344 |
0.0132247451 |
0.0018611087 |
| -11.629207 |
51 |
0.44318182 |
0.43181818 |
-0.197799788 |
0.42160086 |
0.0215809622 |
0.0102173258 |
| -11.312669 |
74 |
0.45454545 |
0.44318182 |
-0.192415834 |
0.42370825 |
0.0308372092 |
0.0194735728 |
| -8.236558 |
3 |
0.46590909 |
0.45454545 |
-0.140094626 |
0.44429261 |
0.0216164775 |
0.0102528411 |
| -7.662789 |
70 |
0.47727273 |
0.46590909 |
-0.130335452 |
0.44815052 |
0.0291222111 |
0.0177585748 |
| -6.752801 |
67 |
0.48863636 |
0.47727273 |
-0.114857588 |
0.45427900 |
0.0343573625 |
0.0229937262 |
| -6.707262 |
31 |
0.50000000 |
0.48863636 |
-0.114083016 |
0.45458599 |
0.0454140074 |
0.0340503710 |
| -6.402439 |
85 |
0.51136364 |
0.50000000 |
-0.108898313 |
0.45664157 |
0.0547220642 |
0.0433584278 |
| -5.446904 |
82 |
0.52272727 |
0.51136364 |
-0.092645733 |
0.46309251 |
0.0596347676 |
0.0482711313 |
| -3.537785 |
43 |
0.53409091 |
0.52272727 |
-0.060173762 |
0.47600862 |
0.0580822876 |
0.0467186512 |
| -2.824941 |
61 |
0.54545455 |
0.53409091 |
-0.048049090 |
0.48083856 |
0.0646159857 |
0.0532523493 |
| -2.745208 |
68 |
0.55681818 |
0.54545455 |
-0.046692922 |
0.48137899 |
0.0754391961 |
0.0640755598 |
| -0.195089 |
65 |
0.56818182 |
0.55681818 |
-0.003318245 |
0.49867621 |
0.0695056040 |
0.0581419676 |
| 1.399296 |
55 |
0.57954545 |
0.56818182 |
0.023800450 |
0.50949411 |
0.0700513452 |
0.0586877088 |
| 5.363331 |
26 |
0.59090909 |
0.57954545 |
0.091224254 |
0.53634280 |
0.0545662924 |
0.0432026561 |
| 6.700640 |
53 |
0.60227273 |
0.59090909 |
0.113970383 |
0.54536936 |
0.0569033628 |
0.0455397265 |
| 7.386314 |
80 |
0.61363636 |
0.60227273 |
0.125632935 |
0.54998875 |
0.0636476093 |
0.0522839730 |
| 9.099900 |
41 |
0.62500000 |
0.61363636 |
0.154779103 |
0.56150227 |
0.0634977329 |
0.0521340965 |
| 12.433611 |
46 |
0.63636364 |
0.62500000 |
0.211481796 |
0.58374433 |
0.0526193043 |
0.0412556680 |
| 16.718018 |
62 |
0.64772727 |
0.63636364 |
0.284354766 |
0.61193074 |
0.0357965328 |
0.0244328965 |
| 18.093192 |
5 |
0.65909091 |
0.64772727 |
0.307744934 |
0.62086179 |
0.0382291219 |
0.0268654856 |
| 18.801816 |
38 |
0.67045455 |
0.65909091 |
0.319797835 |
0.62543921 |
0.0450153400 |
0.0336517036 |
| 19.168108 |
33 |
0.68181818 |
0.67045455 |
0.326028052 |
0.62779843 |
0.0540197476 |
0.0426561112 |
| 19.219211 |
72 |
0.69318182 |
0.68181818 |
0.326897255 |
0.62812720 |
0.0650546167 |
0.0536909803 |
| 20.334434 |
59 |
0.70454545 |
0.69318182 |
0.345865960 |
0.63527827 |
0.0692671805 |
0.0579035442 |
| 24.909926 |
78 |
0.71590909 |
0.70454545 |
0.423689939 |
0.66410402 |
0.0518050676 |
0.0404414312 |
| 26.236229 |
40 |
0.72727273 |
0.71590909 |
0.446248874 |
0.67229126 |
0.0549814685 |
0.0436178321 |
| 30.924022 |
25 |
0.73863636 |
0.72727273 |
0.525982978 |
0.70054998 |
0.0380863808 |
0.0267227444 |
| 32.253952 |
45 |
0.75000000 |
0.73863636 |
0.548603608 |
0.70836125 |
0.0416387548 |
0.0302751184 |
| 32.529367 |
49 |
0.76136364 |
0.75000000 |
0.553288104 |
0.70996693 |
0.0513967091 |
0.0400330727 |
| 32.675968 |
18 |
0.77272727 |
0.76136364 |
0.555781630 |
0.71081993 |
0.0619073452 |
0.0505437088 |
| 33.275839 |
20 |
0.78409091 |
0.77272727 |
0.565984762 |
0.71429793 |
0.0697929786 |
0.0584293423 |
| 36.031430 |
52 |
0.79545455 |
0.78409091 |
0.612854281 |
0.73001365 |
0.0654408934 |
0.0540772571 |
| 37.147186 |
84 |
0.80681818 |
0.79545455 |
0.631832029 |
0.73625168 |
0.0705665028 |
0.0592028664 |
| 40.320875 |
7 |
0.81818182 |
0.80681818 |
0.685812928 |
0.75358446 |
0.0645973596 |
0.0532337232 |
| 44.334467 |
30 |
0.82954545 |
0.81818182 |
0.754079634 |
0.77459930 |
0.0549461574 |
0.0435825211 |
| 46.907165 |
28 |
0.84090909 |
0.82954545 |
0.797838357 |
0.78751785 |
0.0533912405 |
0.0420276041 |
| 54.418366 |
87 |
0.85227273 |
0.84090909 |
0.925595465 |
0.82267187 |
0.0296008528 |
0.0182372164 |
| 55.091131 |
35 |
0.86363636 |
0.85227273 |
0.937038450 |
0.82563061 |
0.0380057535 |
0.0266421172 |
| 55.470305 |
44 |
0.87500000 |
0.86363636 |
0.943487765 |
0.82728426 |
0.0477157353 |
0.0363520989 |
| 62.939597 |
6 |
0.88636364 |
0.87500000 |
1.070532059 |
0.85781006 |
0.0285535797 |
0.0171899433 |
| 66.478628 |
50 |
0.89772727 |
0.88636364 |
1.130727018 |
0.87091500 |
0.0268122757 |
0.0154486394 |
| 67.426518 |
63 |
0.90909091 |
0.89772727 |
1.146849569 |
0.87427810 |
0.0348128083 |
0.0234491719 |
| 67.603959 |
19 |
0.92045455 |
0.90909091 |
1.149867648 |
0.87490081 |
0.0455537393 |
0.0341901029 |
| 69.707122 |
64 |
0.93181818 |
0.92045455 |
1.185640095 |
0.88211777 |
0.0497004123 |
0.0383367759 |
| 69.843246 |
8 |
0.94318182 |
0.93181818 |
1.187955411 |
0.88257451 |
0.0606073068 |
0.0492436705 |
| 74.848732 |
2 |
0.95454545 |
0.94318182 |
1.273093116 |
0.89850750 |
0.0560379553 |
0.0446743189 |
| 112.729191 |
66 |
0.96590909 |
0.95454545 |
1.917397313 |
0.97240626 |
0.0064971714 |
0.0178608078 |
| 163.795081 |
73 |
0.97727273 |
0.96590909 |
2.785970904 |
0.99733162 |
0.0200588896 |
0.0314225260 |
| 198.660139 |
42 |
0.98863636 |
0.97727273 |
3.378986513 |
0.99963623 |
0.0109998685 |
0.0223635048 |
| 209.375830 |
76 |
1.00000000 |
0.98863636 |
3.561248407 |
0.99981545 |
0.0001845478 |
0.0111790885 |
Prueba SW Gráfico
library(fastGraph)
# Calcula los residuos estandarizados
residuos_SW_graph <- scale(modelo_hrpice$residuals)
# Gráfico de la distribución de los residuos
hist(residuos_SW_graph, freq = FALSE, main = "Distribucion de los residuos estandarizados", xlab = "Residuos estandarizados")
# Añade una curva de la distribución normal para comparar
curve(dnorm(x, mean=mean(residuos_SW_graph), sd=sd(residuos_SW_graph)), add=TRUE, col="blue", lwd=2)