On Oct 22, 2010, at 9:01 AM, Dimitri Liakhovitski wrote:
Dear R'ers,
I am fighting with a problem that is driving me crazy. I use "lm" in
my user-defined function, but it seems to be looking for weights
outside of my function's environment:
### Generating example data:
x<-data.frame(y=rnorm(100,0,1),a=rnorm(100,1,1),b=rnorm(100,2,1))
myweights<-runif(100)
data.for.regression<-x[1:3]
### Creating function "weighted.reg":
weighted.reg=function(formula, MyData, filename,WeightsVector)
{
print(dim(MyData))
print(filename)
print(length(WeightsVector))
regr.f<-lm(formula,MyData,weights=WeightsVector,na.action=na.omit)
results<-as.data.frame(round(summary(regr.f)$coeff,3))
write.csv(results,file=filename)
return(results)
}
### Running "weighted.reg" with my data:
reg2<-weighted.reg(y~., MyData=x, WeightsVector=myweights,
filename="TEST.csv")
I get an error: Error in eval(expr, envir, enclos) : object
'WeightsVector' not found
Notice, that the function correctly prints length(WeightsVector). But
it looks like "lm" is looking for weights (in the 4th line of the
function) OUTSIDE the function and does not see WeightsVector.
Have you tried putting WeightsVector in the "x" dataframe? That would
seem to reduce the potential for environmental conflation.
From the details section of help(lm):
"All of weights, subset and offset are evaluated in the same way as
variables in formula, that is first in data and then in the
environment of formula."
Why is it looking outside the function for the object that has just
been defined inside the function?
David Winsemius, MD
West Hartford, CT
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