将 `lm` 结果传递给 `stepAIC` 在脚本中工作,在函数内部失败

Lee*_*ian 5 r function

MASS::stepAIC函数将lm结果作为参数并进行逐步回归以找到“最佳”模型。以下代码非常简单且有效:

library(MASS)
data("mtcars")

lm1 = lm(mpg ~ ., mtcars)
step1 = stepAIC(lm1, direction = "both", trace = FALSE)

Run Code Online (Sandbox Code Playgroud)

我试图把它放在一个函数中。最终我想做更多的事情,但是当包裹在一个函数中时,我什至无法让这两行代码工作:

fit_model = function(formula, data) {
  full_model = lm(formula = formula, data = data)
  step_model = stepAIC(full_model, direction = "both", trace = FALSE)
  return(step_model)
}

step2 = fit_model(mpg ~ ., mtcars)
Run Code Online (Sandbox Code Playgroud)
Error in eval(predvars, data, env) : 
  invalid 'envir' argument of type 'closure' 
Run Code Online (Sandbox Code Playgroud)

我在跑:

R version 3.6.2 (2019-12-12)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Linux Mint 19.1
Run Code Online (Sandbox Code Playgroud)

Rom*_*rik 5

这是你的罪魁祸首(在fit_model函数内)。请注意创建公式的环境。

Browse[1]> str(formula)
Class 'formula'  language mpg ~ .
  ..- attr(*, ".Environment")=<environment: R_GlobalEnv> 
Run Code Online (Sandbox Code Playgroud)

你能做的也许就是在新环境中强行

fit_model = function(formula, data) {
  environment(formula) <- new.env()
  full_model = lm(formula = formula, data = data)
  step_model = stepAIC(full_model, direction = "both", trace = FALSE)
  return(step_model)
}

> step2

Call:
lm(formula = mpg ~ wt + qsec + am, data = data)

Coefficients:
(Intercept)           wt         qsec           am  
      9.618       -3.917        1.226        2.936 
Run Code Online (Sandbox Code Playgroud)