Expands a contingency table to a data frame where each observation in the table becomes a single observation in the data frame with corresponding information for each for each combination of the table dimensions.
screen_variables(x, y, lambda = 0.1, method = c("global-strong", "global-DPP"))
| x | A table or matrix |
|---|---|
| y | A vector of outcomes |
| lambda | a vector of positive values used for the penalization parameter. |
| method | a string giving the method used for screening. Two possibilities are "global-strong" and "global-DPP" |
A list with three elements: lambda which contains the lambda values, selected which contains the indices of the selected variables, and method a string listing the method used.
Note that no standardization is done (not necessary?)
Hastie, Tibshirani and Wainwright (2015). "Statistical Learning with Sparsity". CRC Press.
x <- matrix(rnorm(50*100), nrow=50) y <- rnorm(50, mean=x[,1]) screen_variables(x, y, lambda=c(.1, 1, 2))#> Warning: betingelsen har længde > 1 og kun det første element vil blive brugt#> $lambda #> [1] 0.1 1.0 2.0 #> #> $selected #> integer(0) #> #> $method #> [1] "global-strong" #>