Hello,
Not sure if I understand your question correctly, but you if you want
to assign a value to an object called train in the parent environment
you can do this in your function...
train <<- some.data
Michael
On 20 September 2010 01:10, darckeen <darck...@hotmail.com> wrote:
>
> I'm trying to get the following section of code to work, I think the problem
> is being caused by the assignment of data to the lm function not evaluating
> to "train" in the parent environment but I can't seem to figure out how to
> do this.
>
> fitmodel <- function(trial,data)
> {
> wrap.lm <- function(formula,data,...) { cat("in wrap
> lm",NROW(data),"\n");
> lm(formula,data,...) }
> wrap.step <- function(object,scope,...) { cat("in wrap
> step",NROW(train),"\n"); step(object,scope,...) }
>
> train <- data[1:tr...@n,]
> null <- as.formula("y ~ 1")
> full <- as.formula("y ~ 1 + x1 + x2")
>
> cat("in fit",NROW(train),"\n")
> model <- do.call(tr...@fit$func,tr...@fit$args)
> print(model$call)
> select <- do.call(tr...@step$func,tr...@step$args)
> }
>
> mydf <- data.frame(y <- runif(100),x1 <- runif(100),x2 <- runif(100))
> myfit <- list(func="wrap.lm",args=alist(formula=null,data=train))
> mystep <- list(func="wrap.step",args=alist(object=model,scope=full,trace=0))
>
> setClass("trial",representation(n="numeric",fit="list",step="list"))
> trial1 <- new("trial",n=50,fit=myfit,step=mystep)
> trial2 <- new("trial",n=75,fit=myfit,step=mystep)
>
> result <- lapply(list(trial1,trial2),fitmodel,mydf)
> print(coef(result[[1]]))
> print(coef(result[[2]]))
> cat("result #1",NROW(result[[1]]$model),"\n")
> cat("result #2",NROW(result[[2]]$model),"\n")
>
>
> The resulting output is:
> in fit 50
> in wrap lm 50
> lm(formula = formula, data = data)
> in wrap step 50
> in fit 75
> in wrap lm 75
> lm(formula = formula, data = data)
> in wrap step 75
> (Intercept)
> 0.5276266
> (Intercept)
> 0.5276266
> result #1 100
> result #2 100
>
> I think what is happening is that step is reassigning the "data" for lm to
> the fitmodel environment thus using resulting in using 100 rows. Any ideas
> would be appreciated.
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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