LiPred: Li, Martin Predictions

In AndrewjSage/RFLOWESS: A robust approach to random forest regression

Description

Predictions obtained by reweighting training cases using Li & Martin's (2017) approach

Usage

LiPred(OOBWeights, PredWeights, TRAINY, method = "Huber", delta = 0.005,
  tol = 10^-6, maxiter = 1000)

Arguments

OOBWeights	matrix of OOB training case weights
PredWeights	ntest by ntrain matrix of prediction case weights
TRAINY	vector of training case response values
method	should Tukey or Huber weighting function be used?
delta	value of tuning parameter
tol	maximal tolerance for change between iterations
maxiter	maximum number of iterations

Value

returns a list containing 1- vector of predictions 2- vector of adjusted case weights 3- number of iterations

AndrewjSage/RFLOWESS documentation built on May 26, 2019, 6:38 a.m.