library(leaps)
                                
g
x <- model.matrix(g)[,-1]
y <- statedata$Life
g <- leaps(x,y)
g
Cpplot(g)
plot(g$size,g$Cp)
abline(0,1)
plot(g$size,g$Cp,ylim=c(0,20))
abline(0,1)
g$Cp[size==4]
g$Cp[g$size==4]
g$which$Cp[g$size==4][1]
g$which[g$size==4][1]
g$which[g$size==4][1,]
g$which[g$size==4]
g$which[g$size==4,][1,]
statedata[1:2]
statedata[1:2,]
g
g <- leaps(x,y,method="adjr2")
maxadjr(adjr,8)
g
g$which(g$adjr==max(g$adjr))
g$which[g$adjr==max(g$adjr),]
help(leaps)
h <- hat(x)
names(h) <- state.abb
rev(sort(h))
l <- leaps(x[-2,],y[,-2],method="adjr2")
l <- leaps(x[-2,],y[-2],method="adjr2")
g$which[g$adjr==max(a$adjr),]
l$which[l$adjr==max(l$adjr),]
par(mfrow=c(3,3))
for(i in 1:8) box(state.x77[,i])
for(i in 1:8) boxplot(state.x77[,i])
nx <- cbind(log(x[,1],x[2:6],log(x[,7]))
)
nx <- cbind(log(x[,1],x[,2:6],log(x[,7]))
)
nx <- cbind(log(x[,1]),x[,2:6],log(x[,7]))
a <- leaps(nx,y,methods="adjr2")
a <- leaps(nx,y,method="adjr2")
a$which[a$adjr==max(a$adjr),]