#agrupamientos -clusters- multivariados
setwd("~/Dropbox/Clases_UPJ/Ecosistemas/Alumnos/Datos salida") # selección directorio de trabajo
campo=read.table("cluster.txt", header=T) # lectura de la base de datos
campo2=transform(campo, temp.amb=scale(temp.amb), temp.rocio=scale(temp.rocio), vel.viento=scale(vel.viento), luz=scale(luz), ph=scale(ph), humedad.suelo=scale(humedad.suelo), humedad.amb=scale(humedad.amb)) # estandarizar variables
d <- dist(campo2, method = "euclidean") # matriz de distancias
fit <- hclust(d, method="ward.D") # genera cluster jerarquico
plot(fit) # dibuja el cluster
#componentes de varianza
campo3=read.table("compilada2.txt", header=T) # lectura de la base de datos
campo4=transform(campo3, temp.amb=scale(temp.amb), temp.rocio=scale(temp.rocio), vel.viento=scale(vel.viento), luz=scale(luz), ph=scale(ph), humedad.suelo=scale(humedad.suelo), humedad.amb=scale(humedad.amb)) # estandarizar variables
attach(campo4)
library(lme4)
## Loading required package: Matrix
fit4=lmer(temp.amb ~ 1 + (1 | lugar/sitio))
fit5=lmer(temp.rocio ~ 1 + (1 | lugar/sitio))
fit6=lmer(vel.viento ~ 1 + (1 | lugar/sitio))
fit7=lmer(luz ~ 1 + (1 | lugar/sitio))
fit8=lmer(ph ~ 1 + (1 | lugar/sitio))
fit9=lmer(humedad.suelo ~ 1 + (1 | lugar/sitio))
fit10=lmer(humedad.amb ~ 1 + (1 | lugar/sitio))
summary(fit4)
## Linear mixed model fit by REML ['lmerMod']
## Formula: temp.amb ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 468
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -6.0561 -0.5294 -0.0488 0.5086 3.2982
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.13094 0.3619
## lugar (Intercept) 0.04779 0.2186
## Residual 0.87537 0.9356
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -0.04225 0.21247 -0.199
summary(fit5)
## Linear mixed model fit by REML ['lmerMod']
## Formula: temp.rocio ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 478.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -0.7700 -0.2582 -0.1120 0.0327 11.8851
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.009084 0.09531
## lugar (Intercept) 0.000000 0.00000
## Residual 0.991831 0.99591
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -0.004674 0.083692 -0.056
summary(fit6)
## Linear mixed model fit by REML ['lmerMod']
## Formula: vel.viento ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 467.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.0959 -0.3952 -0.1230 -0.0258 9.2603
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.07361 0.2713
## lugar (Intercept) 0.14842 0.3853
## Residual 0.88236 0.9393
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 0.08052 0.29840 0.27
summary(fit7)
## Linear mixed model fit by REML ['lmerMod']
## Formula: luz ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 383.8
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.7418 -0.5458 -0.1146 0.2257 4.7556
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.6945 0.8334
## lugar (Intercept) 0.1090 0.3302
## Residual 0.4819 0.6942
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 0.1481 0.3722 0.398
summary(fit8)
## Linear mixed model fit by REML ['lmerMod']
## Formula: ph ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 399.9
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3487 -0.4535 0.1740 0.5508 2.3153
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.09937 0.3152
## lugar (Intercept) 0.56235 0.7499
## Residual 0.57183 0.7562
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -0.04318 0.54533 -0.079
summary(fit9)
## Linear mixed model fit by REML ['lmerMod']
## Formula: humedad.suelo ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 433.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.75587 -0.81458 0.04952 0.73412 2.34772
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.29798 0.5459
## lugar (Intercept) 0.07808 0.2794
## Residual 0.68383 0.8269
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -0.07699 0.28056 -0.274
summary(fit10)
## Linear mixed model fit by REML ['lmerMod']
## Formula: humedad.amb ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 452
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.2474 -0.4570 0.0117 0.4259 2.4314
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 2.514e-01 5.014e-01
## lugar (Intercept) 5.716e-16 2.391e-08
## Residual 7.763e-01 8.811e-01
## Number of obs: 168, groups: sitio:lugar, 9; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -0.09524 0.18151 -0.525
#diferencias entre lugares
detach(campo4)
attach(campo3)
fit11=t.test(temp.amb~lugar)
fit11
##
## Welch Two Sample t-test
##
## data: temp.amb by lugar
## t = -1.986, df = 160.65, p-value = 0.04873
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.479266992 -0.004176135
## sample estimates:
## mean in group chingaza mean in group encenillo
## 15.22899 15.97071
fit12=t.test(temp.rocio~lugar)
fit12
##
## Welch Two Sample t-test
##
## data: temp.rocio by lugar
## t = 0.86941, df = 77.182, p-value = 0.3873
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.241367 3.165557
## sample estimates:
## mean in group chingaza mean in group encenillo
## 13.14391 12.18182
fit13=t.test(vel.viento~lugar)
fit13
##
## Welch Two Sample t-test
##
## data: vel.viento by lugar
## t = 2.9143, df = 84.505, p-value = 0.004562
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.2075403 1.0990034
## sample estimates:
## mean in group chingaza mean in group encenillo
## 0.8724638 0.2191919
fit14=t.test(luz~lugar)
fit14
##
## Welch Two Sample t-test
##
## data: luz by lugar
## t = 2.7795, df = 112.29, p-value = 0.006384
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.737572 10.363526
## sample estimates:
## mean in group chingaza mean in group encenillo
## 16.44348 10.39293
fit15=t.test(ph~lugar)
fit15
##
## Welch Two Sample t-test
##
## data: ph by lugar
## t = -8.3989, df = 93.994, p-value = 4.619e-13
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.911202 -0.562755
## sample estimates:
## mean in group chingaza mean in group encenillo
## 5.957971 6.694949
fit16=t.test(humedad.suelo~lugar)
fit16
##
## Welch Two Sample t-test
##
## data: humedad.suelo by lugar
## t = 4.7089, df = 140.32, p-value = 5.917e-06
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 10.76745 26.35157
## sample estimates:
## mean in group chingaza mean in group encenillo
## 67.24638 48.68687
fit17=t.test(humedad.amb~lugar)
fit17
##
## Welch Two Sample t-test
##
## data: humedad.amb by lugar
## t = 1.8799, df = 94.589, p-value = 0.0632
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1973163 7.2319584
## sample estimates:
## mean in group chingaza mean in group encenillo
## 80.10116 76.58384