On Mon, Feb 7, 2011 at 9:21 AM, Joshua Wiley <jwiley.ps...@gmail.com> wrote:
>
> Hi,
> When a function cannot find a variable inside its own environment, it
> will look to its parent environment.
This is false. It will "look to" its **enclosing environment" /
"enclosure" . See
?environment
(Note: This is fundamental to R scoping)
-- Bert
>
> If you define a function in the
> global environment, the global environment is its parent environment.
> However, if you define a function in the global environment, but then
> proceed to use lapply() with another function, the actual variable
> ll() needs to access is neither passed to II (so it is not in its
> environment) nor is it in the global environment (II's parent
> environment). It is in the function in lapply's environment, which is
> inaccessible to II. I have made some small changes to your code that
> gets around this, but I am still not convinced this is really doing
> what you want, but that is a whole other question/problem.
>
> Also, for future reference, you are more likely to get a response/help
> if you mention the required packages. I made educated guesses, that
> you are using mle() from "stats4" and count() from "plyr" (I realize
> you may not even be aware that those functions came from non-default
> loading packages).
>
> HTH,
>
> Josh
>
> Here are my edits to your code:
>
> foo <- function(x) {
> ## load required packages (guessing here)
> require(stats4)
> require(plyr)
>
> ## define ll function _inside_ foo
> ## this is important if you want it to have access
> ## to arguments in foo
> ll <- function(lambda = 1) {
> cat("x in ll()", x, "\n")
> y.fit <- dpois(x, lambda)
> sum( (y - y.fit)^2 )
> }
>
> ## Your calculations
> ## (though I'm not convinced this is what you really want)
> raw.data <- rpois(100, lambda.data[x])
> freqTab <- count(raw.data)
> x <- freqTab$x
> y <- freqTab$freq / sum(freqTab$freq)
>
> cat("x in lapply", x, "\n")
> fit <- mle(ll)
> coef(fit)
> }
>
> ## Data
> lambda.data <- runif(10, 0.5, 10)
> ## Run it through lapply for x = 1:10
> lapply(1:10, FUN = foo)
>
>
> >
> > Here is a little example which show my problem:
> >
> > # R-code ---------------------------------
> >
> > lambda.data <- runif(10,0.5,10)
> >
> > ll <- function(lambda = 1) {
> > cat("x in ll()",x,"\n")
> > y.fit <- dpois(x, lambda)
> >
> > sum( (y - y.fit)^2 )
> >
> > }
> >
> > lapply(1:10, FUN = function(x){
> >
> > raw.data <- rpois(100,lambda.data[x])
> >
> > freqTab <- count(raw.data)
> > x <- freqTab$x
> > y <- freqTab$freq / sum(freqTab$freq)
> > cat("x in lapply", x,"\n")
> > fit <- mle(ll)
> >
> > coef(fit)
> > })
> >
> > Can anybody help?
> >
> > Antje
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
>
>
> --
> Joshua Wiley
> Ph.D. Student, Health Psychology
> University of California, Los Angeles
> http://www.joshuawiley.com/
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Bert Gunter
Genentech Nonclinical Biostatistics
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and provide commented, minimal, self-contained, reproducible code.
