Can you please explain to me why th code complain saying that Samdat is not found? I am trying to switch between the models as you can see, so i declared a functions that contains these specific models and I just need to call these function as one of the argument in the get.f function where the resampling will change the structure for each design matrix in the model. the code complain the Samdat is not found when it is found.

Also, is there a way I can make the condition statement as if(Model == M1()) instead I have to create another argument M to set if(M==1)

Can you explain please?

dat <-  cbind(Y=rnorm(20),rnorm(20),runif(20),rexp(20),rnorm(20),runif(20), rexp(20),rnorm(20),runif(20),rexp(20))
nam <- paste("v",1:9,sep="")
colnames(dat) <- c("Y",nam)

M1 <- function(){
    a1 = cbind(Samdat[,c(2:5,7,9)])
    b1 = cbind(Samdat[,c(2:4,6,8,7)])
    c1 = b1+a1
    list(a1=a1,b1=b1,c1=c1)}

M2 <- function(){
    a1= cbind(Samdat[,c(2:5,7,9)])+2
    b1= cbind(Samdat[,c(2:4,6,8,7)])+2
    c1 = a1+b1
    list(a1=a1,b1=b1,c1=c1)}

M3 <- function(){
    a1= cbind(Samdat[,c(2:5,7,9)])+8
    b1= cbind(Samdat[,c(2:4,6,8,7)])+8
    c1 = a1+b1
    list(a1=a1,b1=b1,c1=c1)}
#################################################################
get.f <- function(asim,Model,M){
    sse <-c()
    for(i in 1:asim){
        set.seed(i)
        Samdat <- dat[sample(1:nrow(dat),nrow(dat),replace=T),]
        Y <- Samdat[,1]
        if(M==1){
            a2 <- Model$a1
            b2 <- Model$b1
            c2 <- Model$c1
            s<- a2+b2+c2
            fit <- lm(Y~s)
            cof <- sum(summary(fit)$coef[,1])
            coff <-Model$cof
            sse <-c(sse,coff)
        }
        else if(M==2){
            a2 <- Model$a1
            b2 <- Model$b1
            c2 <- Model$c1
            s<- c2+12
            fit <- lm(Y~s)
            cof <- sum(summary(fit)$coef[,1])
            coff <-Model$cof
            sse <-c(sse,coff)
        }
        else {
            a2 <- Model$a1
            b2 <- Model$b1
            c2 <- Model$c1
            s<- c2+a2
            fit <- lm(Y~s)
            cof <- sum(summary(fit)$coef[,1])
            coff <- Model$cof
            sse <-c(sse,coff)
        }
    }
    return(sse)
}

get.f(10,Model=M1(),M=1)
get.f(10,Model=M2(),M=2)
get.f(10,Model=M3(),M=3)