[SOLVED] CS代考计算机代写 library(“lmtest”) # for coeftest()

library(“lmtest”) # for coeftest()
library(“MASS”) # for Boston housing data
data(“Boston”)# ?Boston; names(Boston)
# focusing here on a small sample case (n=20):
Boston_small <- Boston[1:20,]lm_obj <- lm(medv ~ ptratio + lstat + nox + crim, data = Boston_small)round(coeftest(lm_obj), 2)#> t test of coefficients:
#>
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 112.5939.862.82 0.01 **
#> ptratio-0.92 1.00 -0.92 0.37
#> lstat-0.47 0.18 -2.57 0.02 *
#> nox-134.7253.73 -2.51 0.02 *
#> crim4.99 8.650.58 0.57
#> —
#> Signif. codes:0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

library(“car”)
linearHypothesis(lm_obj, c(“lstat=0”, “nox=0”))

#> Linear hypothesis test
#>
#> Hypothesis:
#> lstat = 0
#> nox = 0
#>
#> Model 1: restricted model
#> Model 2: medv ~ ptratio + lstat + nox + crim
#>
#> Res.DfRSS Df Sum of SqFPr(>F)
#> 1 17 344.27
#> 2 15 190.402153.88 6.0614 0.01177 *
#> —
#> Signif. codes:0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

install.packages(“sandwich”)
install.packages(“lmtest”)
install.packages(“car”)
install.packages(“AER”)

library(“sandwich”)
library(“lmtest”)
library(“car”)
library(“AER”)