[R] Passing formula and weights error
William Dunlap
wdun|@p @end|ng |rom t|bco@com
Fri Aug 28 18:38:07 CEST 2020
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 <jswhct using 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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