model_fit_answers.R

data1 <- read.csv("data_set_1.csv")
library(MASS)
library(car)
data1a <- within(data1,Y2<-exp(Y))
res <- stepAIC(lm(Y~(X1+X2+X3+X4+X5+X6)^2+I(X1^2)+I(X2^2)+I(X3^2)+I(X4^2)+I(X5^2)+I(X6^2),data=data1),k=log(2010))
plot(res,1)



data2 <- read.csv("data_set_2.csv")
res <- stepAIC(lm(log(Y)~(X1+X2+X3+X4+X5+X6)^2+I(X1^2)+I(X2^2)+I(X3^2)+I(X4^2)+I(X5^2)+I(X6^2),data=data2),
               k=log(6903))
summary(res)
plot(res,1)


data3 <- read.csv("data_set_3.csv")
res <- stepAIC(lm(Y~X1+X2+X3+X4+X5+X6+X7+X8,data=data3),
               k=log(956))
boxTidwell(Y~X1+X3,~X2+X4+X6,data=data3a)
res <- stepAIC(lm(Y~log(X1)+X2+I(X3^2)+X4+I(1/X5)+X6+X7+X8,data=data3),
               k=log(956))
plot(res,1)
summary(res)