我想使用 x 和 ys 的所有可能组合来运行许多模型。我创建了以下代码来执行此操作。
library(tidyverse)
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)))
现在,我想获得原始数据集中所有这些模型的所有预测,这里是 mtcars。我怎样才能做到这一点?有没有办法使用扫帚增强?
您可以使用map
and augment
与您的穿着方式相似glm
到每一行。
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
list.
models2 <- models %>%
select(Formula, Pred) %>%
unnest() %>%
select(`.rownames`, names(mtcars), Formula, `.fitted`) %>%
spread(Formula, `.fitted`)
本文内容由网友自发贡献,版权归原作者所有,本站不承担相应法律责任。如您发现有涉嫌抄袭侵权的内容,请联系:hwhale#tublm.com(使用前将#替换为@)