Add butchering methods for glm()

[juliasilge]

Closes #211

library(butcher)

more_cars <- mtcars[rep(1:32, each = 1000),]
cars_glm <- glm(mpg ~ ., data = more_cars)
weigh(cars_glm)
#> # A tibble: 63 × 2
#>    object             size
#>    <chr>             <dbl>
#>  1 qr.qr             5.36 
#>  2 y                 2.80 
#>  3 residuals         2.80 
#>  4 fitted.values     2.80 
#>  5 linear.predictors 2.80 
#>  6 weights           2.80 
#>  7 prior.weights     2.80 
#>  8 effects           0.513
#>  9 model.mpg         0.256
#> 10 model.cyl         0.256
#> # … with 53 more rows

butchered <- butcher(cars_glm)
sum(weigh(cars_glm)$size)
#> [1] 28.325
sum(weigh(butchered)$size)
#> [1] 11.75713
weigh(butchered)
#> # A tibble: 53 × 2
#>    object             size
#>    <chr>             <dbl>
#>  1 linear.predictors 2.80 
#>  2 weights           2.80 
#>  3 prior.weights     2.80 
#>  4 effects           0.513
#>  5 model.mpg         0.256
#>  6 model.cyl         0.256
#>  7 model.disp        0.256
#>  8 model.hp          0.256
#>  9 model.drat        0.256
#> 10 model.wt          0.256
#> # … with 43 more rows

^{Created on 2022-02-08 by the reprex package (v2.0.1)}

As far as I can tell, the linear.predictors and weights components are needed to make a prediction but it's very possible I missed something.

[juliasilge]

The older versions of R are failing because of randomForest. We'll have to figure out what to do about that.

[github-actions]

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