访问 R 中模型对象内的估计值

Question

我正在运行一个模拟，想知道是否可以使用 broom、dplyr、modelr 或 purrr 访问我的模型内部的“x”估计值。

这正是我想要的，但我不想在最后一段代码中使用[[1]]。

library(tidyverse)
library(purrr)
library(broom)
mod <- function(df) {
  lm(y ~ x, data = df)
}
sim <- tibble(
model = "model1",
mu = 5,             #this is unknown in practice                         
beta = 2.7,         #this is unknown in practice
sigma = 0.15,       #this is unknown in practice
mu_e = 0,
sigma_e = 1
)
sim_dat <- sim %>% 
crossing(replication = 1:10000) %>%
mutate(e = rnorm(mu_e, mu_e),
       x = sample(c(0,1),size=n(),replace = TRUE,prob=c(0.5, 0.5)),
       y = mu+x*beta+e) %>% 
  group_by(model) %>% 
  nest() %>% 
  mutate(model_fit = map(data, mod)) 

broom::tidy(sim_dat$model_fit[[1]]) %>% 
  filter(term=="x") %>% 
  select(estimate)

Answer 1

你可以使用purrr::map_df():

map_df(sim_dat$model_fit, broom::tidy) %>% 
    filter(term=="x") %>% 
    select(estimate)

您也可以像这样将其放入mutate(model_fit = ...)：

sim_dat <- sim %>% 
    crossing(replication = 1:10000) %>%
    mutate(e = rnorm(mu_e, mu_e),
           x = sample(c(0,1),size=n(),replace = TRUE,prob=c(0.5, 0.5)),
           y = mu+x*beta+e) %>% 
    group_by(model) %>% 
    nest() %>% 
    mutate(model_fit = map(data, mod),

           # you can pipe inside of mutate()

           x_coef = map_dbl(model_fit, ~broom::tidy(.) %>%
               filter(term =="x") %>% 
               select(estimate) %>%
               unlist() ) ) 

根据您要为 x_coef 返回的对象类别，您可以使用 map_suffix() 并可能放弃 unlist() 我只是认为 dbl 有意义。