ge <- lm.ridge(Employed~.,longley,lambda=seq(0,0.1,0.001))
ge
 matplot(gr$lambda,t(gr$ceof),type="l")
 matplot(ge$lambda,t(ge$ceof),type="l")
 matplot(ge$lambda,t(ge$coef),type="l")
abline(h=0,lwd=2)
select(ge)
gr$coef[,gr$lam==0.03]
ge$coef[,ge$lam==0.03]
abline(v=0.00428)
abline(v=0.032)
data(state)
statedata <- data.frame(state.x77,row.names=state.abb,check.names=T)
statedata
g <- lm(Life.Exp~.,data=statedata)
summary(g)
g <- update(g,.~.,-Area)
summary(g)
g <- update(g,.~.-Area)
summary(g)
g <- update(g,.~.-Illiteracy)
summary(g)
g <- update(g,.~.-Income)
summary(g)
help(stepwise)
help(lm)
 help(step)
g <- lm(Life.Exp~.,data=statedata)
step(g,direction="backward")
step(g,direction="forward")
g <- lm(Life.Exp~1,data=statedata)
g
step(g,direction="forward")
help(step)
g <- lm(Life.Exp~.,data=statedata)
step(g,direction="backward")
step(g,direction="forward")
g <- lm(Life.Exp~1,data=statedata)
g
step(g,direction="forward")
help(step)
g <- lm(Life.Exp~.,data=statedata)
step(g,direction="both")