在R中的data.table环境中创建一个公式

I would like to run a regression within a data.table. The formula needs to be constructed dynamically. I have tried the following method:

我想在data.table中运行回归。公式需要动态构建。我尝试了以下方法：

x = data.table(a=1:20, b=20:1, id=1:5)
> x[,as.list(coef(lm(as.formula("a ~ b")))),by=id]
  Error in eval(expr, envir, enclos) : object 'a' not found

How does one specify the environment to be that of the actual data.table where the evaluation occurs?

如何将环境指定为进行评估的实际data.table的环境？

EDIT: I realize I can do lm(a ~ b). I need the formula to be dynamic so it's built up as a character string. By dynamically I mean the formula can be paste0(var_1, "~", var_2) where var_1 = a and var_2 = b

编辑：我意识到我可以做lm（a~b）。我需要公式是动态的，所以它被构建为一个字符串。通过动态我的意思是公式可以是paste0（var_1，“〜”，var_2）其中var_1 = a和var_2 = b

Here is one solution thought I think we can do better:

这是一个解决方案，我认为我们可以做得更好：

txt = parse(text="as.list(coef(lm(a ~ b)))")
> x[,eval(txt),by=id]
  id (Intercept)  b
  1:  1          21 -1
  2:  2          21 -1
  3:  3          21 -1
  4:  4          21 -1
  5:  5          21 -1

1 个解决方案

#1

lm can accept a character string as the formula so combine that with .SD like this:

lm可以接受一个字符串作为公式，所以将它与.SD结合如下：

> x[, as.list(coef(lm("a ~ b", .SD))), by = id]
   id (Intercept)  b
1:  1          21 -1
2:  2          21 -1
3:  3          21 -1
4:  4          21 -1
5:  5          21 -1