parse variables to lm in r

In R, the lm() function is used to fit linear regression models. It takes a formula and a dataset, and returns an object of class "lm".

To parse variables to lm(), the simplest method is to write a formula where the dependent variable is on the left-hand side and the independent variables are on the right-hand side, separated by the + operator.

Here is an example code snippet that demonstrates how to use lm():

main.r
# Read data from a CSV file
data <- read.csv("my_data.csv")

# Fit a linear regression model using lm()
my_model <- lm(dependent_variable ~ independent_variable1 + independent_variable2, data)

# Print the summary of the model
summary(my_model)
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In the above code snippet, replace "dependent_variable", "independent_variable1", and "independent_variable2" with the actual names of your variables. Also, replace "my_data.csv" with the actual file name/path where your data is stored.

Note that the lm() function assumes that your data is in a data.frame or a tibble format. If your data is in a different format, such as a matrix, you may need to convert it to a data.frame first using the as.data.frame() function.