lm.compare.method: Get fitted models by fitting some variable selection methods

In christineyuen/VSC: Variable selection by combining method fits (VSC)

Description

Get fitted models by fitting some variable selection methods

Usage

lm.compare.method(X, Y, intercept, method.names = NULL)

Arguments

X	covariates (n times p matrix, n: number of entries, p: number of covariates)
Y	response (vector with n entries)
intercept	TRUE to fit the data with an intercept, FALSE to fit the data without an intercept
method.names	vector of method names to be used for fitting. Choose among "lasso", "elastic", "relaxo", "mcp" and "scad". Default is to fit the data using all methods listed above

Value

estimated coefficients in a form of matrix. Each row corresponds to a method and each column corresponds to a covariate, with the first column corresponds to the intercept

Examples

X = matrix(rnorm(1000), nrow = 100)
Y = rowSums(X[,1:3])+rnorm(100)
compare.mod = lm.compare.method(X, Y, intercept = FALSE)
print(compare.mod)

christineyuen/VSC documentation built on Oct. 8, 2019, 10:45 a.m.