[R] Strange scope problem

[Roger D. Peng]

I believe this was fixed in 1.7.0, although I'm not sure of all the 
details.  The NEWS file says

    o   step(), add1.default() and drop1.default() now work somewhat
        better if called from a function.


-roger

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
>
>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 |
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