[R] Strange scope problem

[Uwe Ligges]

Angelo Canty wrote:

> Hi,
> 
> I have come across the following problem which seems to be a scoping
> issue but I'm at a loss to see why this is so or to find a good
> workaround.
> 
> Suppose I have a function to get a prediction after model selection
> using the step function.
> 
> step.pred <- function(dat, x0) {
>   fit.model <- step(lm(y~., data=dat), trace=F)
>   predict(fit.model, x0, se.fit=T)
> }
> 
> This function works sometimes for example
> 
> set.seed(1)
> X.1 <- data.frame(x1=rnorm(20), x2=rnorm(20), x3=rnorm(20))
> y.1 <- 5+as.matrix(X.1[,1:2])%*%matrix(c(1,1))+rnorm(20)
> Xy.1 <- data.frame(X.1,y=y.1)
> x0.1 <- data.frame(x1=-1,x2=-1, x3=-1)
> step.pred(Xy.1, x0.1)
> 
> $fit
> [1] 3.359540
> 
> $se.fit
> [1] 0.523629
> 
> $df
> [1] 16
> 
> $residual.scale
> [1] 1.093526
> 
> but most often it crashes as in

It does not crash. Your outdated version reports an error. R-1.8.0 does 
not. So please upgrade!

Uwe Ligges


> set.seed(2)
> X.2 <- data.frame(x1=rnorm(20), x2=rnorm(20), x3=rnorm(20))
> y.2 <- 5+as.matrix(X.2[,1:2])%*%matrix(c(1,1))+rnorm(20)
> Xy.2 <- data.frame(X.2,y=y.2)
> x0.2 <- data.frame(x1=-1,x2=-1, x3=-1)
> step.pred(Xy.2, x0.2)
> Error in model.frame.default(formula = y ~ x1 + x2, data = dat,
> drop.unused.levels = TRUE) : 
>         Object "dat" not found
> 
> The difference seems to be that for the first dataset, step retains
> all three variables whereas for the second it drops one of them.
> 
> 
>>step(lm(y~.,data=Xy.1), trace=F)
> 
> 
> Call:
> lm(formula = y ~ x1 + x2 + x3, data = Xy.1)
> 
> Coefficients:
> (Intercept)           x1           x2           x3  
>      4.8347       0.8937       1.0331      -0.4516  
> 
> 
>>step(lm(y~.,data=Xy.2), trace=F)
> 
> 
> Call:
> lm(formula = y ~ x1 + x2, data = Xy.2)
> 
> Coefficients:
> (Intercept)           x1           x2  
>      5.0802       0.9763       1.1369  
> 
> 
> One possible workaround is to explicitely assign the local variable
> dat in the .GlobalEnv as in
> 
> step.pred1 <- function(dat, x0) {
>   assign("dat",dat, envir=.GlobalEnv)
>   fit.model <- step(lm(y~., data=dat), trace=F)
>   predict(fit.model, x0, se.fit=T)
> }
> 
> I don't like this method since it would overwrite anything else called
> dat in .GlobalEnv.  I realize that I could give it an obscure name but
> the potential for damage still remains.  Am I missing something obvious
> here?  If not, is it possible to work around this problem in such a way
> that .GlobalEnv does not need to be touched?
> 
> In S-Plus I would use 
> assign("dat",dat, frame=1)
> which works but that is not available (AFAIK) in R.  Is there
> something similar that I can use?
> 
> I am using R 1.6.1 for Unix on a Sun Workstation. I know that I need
> to upgrade but our sysadmin doesn't regard it as priority!  
 >
> Thanks for any help you can give for this.
> Angelo
> 
> ------------------------------------------------------------------
> |   Angelo J. Canty                Email: cantya at mcmaster.ca     |
> |   Mathematics and Statistics     Phone: (905) 525-9140 x 27079 |
> |   McMaster University            Fax  : (905) 522-0935         |
> |   1280 Main St. W.                                             |
> |   Hamilton ON L8S 4K1                                          |
> 
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