sparsereg3D.sel: Model Selection based on Cross-Validation

Description Usage Arguments Value

View source: R/sparsereg3D.sel.r

Description

Model Selection based on Cross-Validation

Usage

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sparsereg3D.sel(sparse.reg, lambda = 0, ols = FALSE, step = FALSE,
  lambda.1se = FALSE)

Arguments

sparse.reg

output from pre.sparsereg3D function

lambda

vector of regularization parameter values for lasso regression

ols

logical. If TRUE model will be fitted with OLS insted of using lasso

step

logical. If TRUE stepwise procedure will be used when fitting OLS model

lambda.1se

logical. If TRUE one sigma lambda rule will be used (largest lambda value with cv.err less than or equal to min(cv.err)+ SE).

seed

random number generator

Value

List of objects including:

@keywords Model selection


pejovic/sparsereg3D documentation built on May 25, 2019, 12:45 a.m.