[R] weighted regression inside FOREACH loop

[Thierry Onkelinx]

Dear Roger,

Maybe you want to return(mod) instead of return(mod$coef)

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

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what the experiment died of. ~ Sir Ronald Aylmer Fisher
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2016-10-07 15:24 GMT+02:00 Bos, Roger <roger.bos op rothschild.com>:

> I have a foreach loop that runs regressions in parallel and works fine,
> but when I try to add the weights parameter to the regression the
> coefficients don’t get stored in the “models” variable like they are
> supposed to.  Below is my reproducible example:
>
> library(doParallel)
> cl <- makeCluster(4)
> registerDoParallel(cl)
> fmla <- as.formula("y ~ .")
> models <- foreach(d=1:10, .combine=rbind, .errorhandling='remove') %dopar%
> {
>   datdf <- data.frame(y = 1:100+2*rnorm(100), x = 1:100+rnorm(100))
>   weights <- rep(c(1,2), 50)
>   mod <- lm(fmla, data=datdf, weights=weights)
>   #mod <- lm(fmla, data=datdf)
>   return(mod$coef)
> }
> models
>
> You can change the commenting on the two “mod <-“ lines to see that the
> non-weighted one works and the weighted regression doesn’t work.  I tried
> using .export="weights" in the foreach line, but R says that weights is
> already being exported.
>
> Thanks in advance for any suggestions.
>
>
>
>
>
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