| alasso {ARGOS} | R Documentation |
Adaptive Lasso
Description
This function performs adaptive lasso regression using the cv.glmnet function, then refits the model using ordinary least squares.
Usage
alasso(data, index, weights_method = c("ols", "ridge"), ols_ps = TRUE)
Arguments
data |
A data frame or matrix containing the predictors and response. The response must be in the first column. |
index |
A numeric vector of indices indicating the rows of 'data' to use for the adaptive lasso regression. |
weights_method |
A character string specifying the method to calculate the weights. Can be either "ols" or "ridge". Default is "ols". |
ols_ps |
A logical scalar. If TRUE (default), the function returns the coefficients from the OLS fit. If FALSE, it returns the coefficients from the lasso fit. |
Value
A numeric vector of coefficients. If 'ols_ps' is TRUE, these are the coefficients from the OLS fit. If 'ols_ps' is FALSE, these are the coefficients from the lasso fit. If an error occurs during the lasso or OLS fit, the function returns a vector of NAs.