从原始数据集中的许多模型增加预测

你可以使用 map 和 augment 与你的身材相似 glm 每一行。

library(tidyverse)
library(broom)

y <- names(mtcars)

xs <- map(y, ~setdiff(names(mtcars), .x)) %>% 
  map(~paste0(.x, collapse = "+")) %>%
  unlist()

ys <- names(mtcars)

models <- tibble(ys, xs) %>%
  mutate(Formula = paste0(ys, " ~ ", xs)) %>% 
  mutate(model = map(Formula, ~glm(as.formula(.x), data = mtcars))) %>%
  mutate(Pred = map(model, augment))

预测是在 .fitted 每个数据帧中的列 Pred 名单。

models2 <- models %>%
  select(Formula, Pred) %>%
  unnest() %>%
  select(`.rownames`, names(mtcars), Formula, `.fitted`) %>%
  spread(Formula, `.fitted`)