L2BoostOGA: Implementation of the orthogonal L2Boosting algorithm

In newboost: New boosting algorithms

Description

This function implements an orthogonal projection version of the L2Boosting algorithm.

Usage

L2BoostOGA(X, y, iter = 200)

Arguments

X	matrix of regressors
y	dependent variable
iter	number of iterations

Value

The functions returns an object of class L2Boost with the following components:

• BetaFinalthe estimated final parameter vector.

• BetaFinal0the estimated final parameter vector of the orthogonal boosting algorithm.

• BetaVectorvector where each component gives the values of the estimated coefficient in each round.

• Resmatrix with the estimated function values in each round

• Res_betamatrix with the estimated coefficient vectors from each round

• iIteration when the process was terminated.

• Svector of the indices of the selected variables in each round

• sigma2estimation of the variance

• stop_ruleWhen the stopping rule, stopped the algorithm.

• itermaximal number of iterations of the algorithm

• ymodel response / dependent variable

• Xmodel matrix

newboost documentation built on May 2, 2019, 5:17 p.m.