Thanks to Duncan and Bill for very helpful tips.
On Fri, Aug 28, 2020 at 11:38 AM William Dunlap <wdun...@tibco.com> wrote:
> Note that neither call to glm in your myglm function really works -
> the first one is using the 'weights' object from the global
> environment, not the weights argument. E.g., in the fresh R session,
> where I avoid making unneeded assignments and use fixed x and y for
> repeatability,
>
> > n <- 16
> > data <- data.frame(x = log2(1:n), y = 1:n)
> > myglm2 <- function(formula, data, weights)
> {
> glm(formula, data=data, family=gaussian(), weights=weights)
> }
> > myglm2(y~., data=data, weights=1/(1:n))
> Error in model.frame.default(formula = formula, data = data, weights
> = weights, :
> invalid type (closure) for variable '(weights)'
>
> The error arises because glm finds stats::weights, a function, not the
> argument called weights. glm(), lm() and their ilk evaluate their
> weights and subset arguments in the environment of the formula. In
> this case environment(y~.) is .GlobalEnv, not the function's
> environment. The following function gives one way to deal with this,
> by giving formula a new environment that inherits from its original
> environment and contains the extra variables.
>
> > myglm3 <- function(formula, data, weights)
> {
> envir <- list2env(list(weights=weights),
> parent=environment(formula))
> environment(formula) <- envir
> glm(formula, data=data, family=gaussian(), weights=weights)
> }
> > myglm3(y~., data=data, weights=1/(1:n))
>
> Call: glm(formula = formula, family = gaussian(), data = data,
> weights = weights)
>
> Coefficients:
> (Intercept) x
> -0.09553 2.93352
>
> Degrees of Freedom: 15 Total (i.e. Null); 14 Residual
> Null Deviance: 60.28
> Residual Deviance: 7.72 AIC: 70.42
>
> This is the same result you get with a direct call to
> glm(y~., data=data, weights=1/(1:n))
>
> This is a common problem and I don't know if there is a FAQ on it or a
> standard function to deal with it.
>
> Bill Dunlap
> TIBCO Software
> wdunlap tibco.com
>
> On Fri, Aug 28, 2020 at 8:33 AM John Smith <jsw...@gmail.com> wrote:
> >
> > Dear R-help:
> >
> > I am writing a function based on glm and would like some variations of
> > weights. In the code below, I couldn't understand why the second glm
> > function fails and don't know how to fix it:
> >
> > Error in eval(extras, data, env) : object 'newweights' not found
> > Calls: print ... eval -> <Anonymous> -> model.frame.default -> eval ->
> eval
> > Execution halted
> >
> > ### R code
> > y <- rnorm(100)
> > x <- rnorm(100)
> > data <- data.frame(cbind(x, y))
> > weights <- rep(1, 100)
> > n <- 100
> > myglm <- function(formula, data, weights){
> > ## this works
> > print(glm(formula, data, family=gaussian(), weights))
> > ## this is not working
> > newweights <- rep(1, n)
> > glm(formula, data, family=gaussian(), weights=newweights)
> > }
> > myglm(y~., data, weights)
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
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> > 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.
>
[[alternative HTML version deleted]]
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