#agrupamientos -clusters- multivariados
campo=read.table("cluster.txt", header=T) # lectura de la base de datos
campo2=transform(campo, temp.suelo=scale(temp.suelo), luz=scale(luz), ph=scale(ph), humedad.suelo=scale(humedad.suelo), temp.org=scale(temp.org), altura.veg=scale(altura.veg), covertura=scale(covertura) ) # estandarizar variables
d <- dist(campo2, method = "euclidean") # matriz de distancias
## Warning in dist(campo2, method = "euclidean"): NAs introducidos por
## coerción
fit <- hclust(d, method="ward.D") # genera cluster jerarquico
plot(fit) # dibuja el cluster
#componentes de varianza
campo3=read.table("promedios.txt", header=T) # lectura de la base de datos
campo4=transform(campo3, temp.suelo=scale(temp.suelo), luz=scale(luz), ph=scale(ph), humedad.suelo=scale(humedad.suelo), temp.org=scale(temp.org), altura.veg=scale(altura.veg), covertura=scale(covertura)) # estandarizar variables
attach(campo4)
library(lme4)
## Warning: package 'lme4' was built under R version 3.3.2
## Loading required package: Matrix
fit4=lmer(temp.suelo ~ 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(temp.org ~ 1 + (1 | lugar/sitio))
fit11=lmer(altura.veg ~ 1 + (1 | lugar/sitio))
fit12=lmer(covertura ~ 1 + (1 | lugar/sitio))
summary(fit4)
## Linear mixed model fit by REML ['lmerMod']
## Formula: temp.suelo ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 74.5
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.18196 -0.51388 0.01091 0.51617 2.01357
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 7.193e-01 8.481e-01
## lugar (Intercept) 6.899e-17 8.306e-09
## Residual 3.503e-01 5.919e-01
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -8.122e-17 3.176e-01 0
summary(fit7)
## Linear mixed model fit by REML ['lmerMod']
## Formula: luz ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 78.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.8395 -0.3875 -0.0760 0.2737 3.2220
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.1811 0.4256
## lugar (Intercept) 0.6592 0.8119
## Residual 0.4962 0.7044
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -9.873e-16 6.064e-01 0
summary(fit8)
## Linear mixed model fit by REML ['lmerMod']
## Formula: ph ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 73.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4479 -0.3080 0.1109 0.5633 1.4791
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.2551 0.5051
## lugar (Intercept) 0.7306 0.8548
## Residual 0.3925 0.6265
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -1.448e-15 6.399e-01 0
summary(fit9)
## Linear mixed model fit by REML ['lmerMod']
## Formula: humedad.suelo ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 77.6
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.22708 -0.57634 0.09505 0.75063 1.84102
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.2425 0.4925
## lugar (Intercept) 0.6126 0.7827
## Residual 0.4648 0.6817
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) 4.194e-15 5.926e-01 0
summary(fit10)
## Linear mixed model fit by REML ['lmerMod']
## Formula: temp.org ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 85.4
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.4984 -0.5400 -0.1636 0.1525 2.5861
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.0000 0.0000
## lugar (Intercept) 0.4603 0.6784
## Residual 0.7624 0.8732
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -3.328e-16 5.039e-01 0
summary(fit11)
## Linear mixed model fit by REML ['lmerMod']
## Formula: altura.veg ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 88
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.3630 -0.7004 -0.3106 0.6376 2.4500
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.04525 0.2127
## lugar (Intercept) 0.29336 0.5416
## Residual 0.80772 0.8987
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -5.065e-16 4.214e-01 0
summary(fit12)
## Linear mixed model fit by REML ['lmerMod']
## Formula: covertura ~ 1 + (1 | lugar/sitio)
##
## REML criterion at convergence: 80
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.3475 -0.6238 -0.2472 0.4757 1.8662
##
## Random effects:
## Groups Name Variance Std.Dev.
## sitio:lugar (Intercept) 0.5050 0.7106
## lugar (Intercept) 0.1563 0.3954
## Residual 0.4632 0.6806
## Number of obs: 32, groups: sitio:lugar, 8; lugar, 2
##
## Fixed effects:
## Estimate Std. Error t value
## (Intercept) -2.053e-16 3.947e-01 0
#diferencias entre lugares
detach(campo4)
attach(campo3)
fit13=t.test(temp.suelo~lugar)
fit13
##
## Welch Two Sample t-test
##
## data: temp.suelo by lugar
## t = 0.47925, df = 25.694, p-value = 0.6358
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -1.219767 1.960912
## sample estimates:
## mean in group bosque mean in group paramo
## 10.072292 9.701719
fit14=t.test(luz~lugar)
fit14
##
## Welch Two Sample t-test
##
## data: luz by lugar
## t = 4.2842, df = 16.296, p-value = 0.0005477
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 5.227039 15.436711
## sample estimates:
## mean in group bosque mean in group paramo
## 15.508437 5.176563
fit15=t.test(ph~lugar)
fit15
##
## Welch Two Sample t-test
##
## data: ph by lugar
## t = 4.6865, df = 28.659, p-value = 6.214e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.4242842 1.0819658
## sample estimates:
## mean in group bosque mean in group paramo
## 6.484375 5.731250
fit16=t.test(humedad.suelo~lugar)
fit16
##
## Welch Two Sample t-test
##
## data: humedad.suelo by lugar
## t = 4.1298, df = 26.364, p-value = 0.0003258
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 0.1110428 0.3308322
## sample estimates:
## mean in group bosque mean in group paramo
## 0.7109375 0.4900000
fit17=t.test(temp.org~lugar)
fit17
##
## Welch Two Sample t-test
##
## data: temp.org by lugar
## t = 3.2648, df = 16.053, p-value = 0.00485
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.653811 7.773689
## sample estimates:
## mean in group bosque mean in group paramo
## 6.84000 2.12625
fit18=t.test(altura.veg~lugar)
fit18
##
## Welch Two Sample t-test
##
## data: altura.veg by lugar
## t = -2.5949, df = 27.707, p-value = 0.01496
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -24.653322 -2.895657
## sample estimates:
## mean in group bosque mean in group paramo
## 40.88698 54.66147
fit19=t.test(covertura~lugar)
fit19
##
## Welch Two Sample t-test
##
## data: covertura by lugar
## t = -2.3974, df = 24.06, p-value = 0.02463
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -38.80903 -2.90347
## sample estimates:
## mean in group bosque mean in group paramo
## 29.14375 50.00000