线性回归中使用的显式公式

我有一个公式列表，我使用lapply and lm创建回归模型列表。然而，当我看到call每个线性模型的组成部分，我看到的不是显式公式，而是解析到线性模型中的变量的名称。例如。使用 mtcars 数据集：

temp_formula_list = list(as.formula(hp~1),as.formula(hp~cyl))
temp_fm_list = lapply(temp_formula_list, function(x) lm(data = mtcars, formula = x))

然后检查call of temp_fm_list[[2]]:

temp_fm_list[[2]]$call

gives

lm(formula = x, data = mtcars)

当我希望它明确给出

lm(formula = hp~cyl, data = mtcars)

您可以使用该语言对该语言进行一些简单的计算bquote构建您的通话。

 temp_fm_list = lapply(temp_formula_list, function(x) {
  lmc <- bquote( lm(data = mtcars, formula = .(x)))
  eval(lmc)                                                      
  })
temp_fm_list
# Call:
#   lm(formula = hp ~ 1, data = mtcars)
# 
# Coefficients:
#   (Intercept)  
# 146.7  
# 
# 
# [[2]]
# 
# Call:
#   lm(formula = hp ~ cyl, data = mtcars)
# 
# Coefficients:
#   (Intercept)          cyl  
# -51.05        31.96  

注意

function(x) do.call('lm', list(formula = x, data = quote(mtcars))

也会工作

其他方法....

即使使用您最初的调用，您也可以从以下内容重新创建公式：terms与模型关联的对象

eg

x <- hp ~ cyl

lmo <- lm(formula = x, data = mtcars)

formula(lmo)
## hp ~ cyl

lmo$call 


# lm(formula = x, data = mtcars)

你可以搞乱这个call如果你愿意的话可以反对（尽管这是相当危险的做法）

# for example

lmo$call$formula <- x
lmo$call 
##  lm(formula = hp ~ cyl, data = mtcars)

## however you can create rubbish here too
lmo$call$formula <- 'complete garbage'
lmo$call 
## lm(formula = "complete garbage", data = mtcars)

# but, being careful, you could use it appropriately
temp_fm_list = lapply(temp_formula_list, function(x) {
  oo <- lm(data = mtcars, formula = x)
  oo$call$formula <-x
  oo
})

temp_fm_list
# Call:
#   lm(formula = hp ~ 1, data = mtcars)
# 
# Coefficients:
#   (Intercept)  
# 146.7  
# 
# 
# [[2]]
# 
# Call:
#   lm(formula = hp ~ cyl, data = mtcars)
# 
# Coefficients:
#   (Intercept)          cyl  
# -51.05        31.96