Dominik Dominik - 2 months ago 24
R Question

bootstrap by group and calculate statistics

I'm trying to bootstrap some model fits and then calculate statistics without having to rerun the models every time. I can do this fine if I calculate r2 inside the first do() but I'd like to know how to access the data.

library(dplyr)
library(tidyr)
library(modelr)
library(purrr)

allmdls <-
mtcars %>%
group_by(cyl) %>%
do({
datsplit=crossv_mc(.,10)
mdls=list(map(datsplit$train, ~glm(hp~disp,data=.,family=gaussian(link='identity'))))
data_frame(datsplit=list(datsplit),mdls)
})


and now something like:

allmdls %>%
by_slice(dmap,.f=map2_dbl(.$mdls,.$datsplit$test,rsquare))


but I get

Error: `.y` is not a vector (NULL)


or

allmdls %>%
group_by(cyl) %>%
do({
map2_df(.x=.$mdls, .y=.$datsplit, .f=map2_dbl(.x=.x,.y=.y$test,.f=rsquare))
})

Error in map2_dbl(.x = .x, .y = .y$test, .f = rsquare) :
object '.x' not found


I can't seem to get the syntax right.

help?
Thanks

EDIT:
Thanks to @aosmith's comment, I created a somewhat simpler solution:

mtcars %>%
group_by(cyl) %>%
do({
datplit=crossv_mc(.,10) %>%
mutate(mdls=map(train, ~glm(hp~disp,data=.)),
r2=map2_dbl(mdls,test,rsquare)
pctmae=map2_dbl(mdls,test,function(model,data) {mae(model,data)/mean(model$model$hp,na.rm=T)*100})
)
})

Answer

One option is to use map2 within mutate. Because you are using lists of lists I ended up with nested map2s to get access to the innermost lists. I pulled the test data out via map(datsplit, "test"), as neither the dollar sign operator nor the extract brackets were working for me.

mutate(allmdls, rsq = map2(mdls, map(datsplit, "test"), ~map2_dbl(.x, .y, rsquare)))
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