通过R中的LM模型的变量列表创建循环 [英] Creating a loop through a list of variables for an LM model in R

问题描述

我正在尝试从变量组合列表中创建多个线性回归模型(如果更有用的话，我也将它们分别作为数据框使用！)

I am trying to create multiple linear regression models from a list of variable combinations (I also have them separately as a data-frame if that is more useful!)

变量列表如下:

Vars
x1+x2+x3
x1+x2+x4
x1+x2+x5
x1+x2+x6
x1+x2+x7

我正在使用的循环如下:

The loop I'm using looks like this:

for (i in 1:length(var_list)){
  lm(independent_variable ~ var_list[i],data = training_data)
  i+1
}

但是，它无法识别出将x1+x2+x3等作为模型输入的var_list[i]字符串.

However it is not recognizing the string of var_list[i] which gives x1+x2+x3 etc. as a model input.

有人知道如何解决吗?

感谢您的帮助.

推荐答案

您甚至不必使用循环. Apply应该能很好地工作.

You don't even have to use loops. Apply should work nicely.

training_data <- as.data.frame(matrix(sample(1:64), nrow = 8))
colnames(training_data) <- c("independent_variable", paste0("x", 1:7))

Vars <- as.list(c("x1+x2+x3",
                "x1+x2+x4",
                "x1+x2+x5",
                "x1+x2+x6",
                "x1+x2+x7"))

allModelsList <- lapply(paste("independent_variable ~", Vars), as.formula)
allModelsResults <- lapply(allModelsList, function(x) lm(x, data = training_data))  

如果需要模型摘要，可以添加:

If you need models summaries you can add :

allModelsSummaries = lapply(allModelsResults, summary) 

例如，您可以通过执行以下操作来访问模型lm(independent_variable ~ x1+x2+x3)的系数R²:

For example you can access the coefficient R² of the model lm(independent_variable ~ x1+x2+x3) by doing this:

allModelsSummaries[[1]]$r.squared

希望对您有帮助.

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