访问 R 中模型对象内的估计值

Question

我正在运行一个模拟，想知道是否有办法使用扫帚、dplyr、modelr 或 purrr 访问模型内部的"x"估计。

这给了我我想要的，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

您可以使用purrr::map_df()：

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

您也可以将其放入mutate(model_fit = ...)中，如下所示：

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() ) ) 

根据您要返回的对象类别x_coef，您可以随map_suffix()四处闲逛，并可能放弃我认为dbl有意义的unlist()。