CppLHS: This is the internal Cpp function used to run the metropolis...

In clhs: Conditioned Latin Hypercube Sampling

Description

This is the internal Cpp function used to run the metropolis hasting algorithm if use.cpp = T. In general, it shouldn't be used as a stand alone function, because some preprocessing is done in R

Arguments

xA	matrix of data - must be numeric (factors are converted to numeric in R)
cost	cost vector (0 if no cost)
strata	matrix of continuous strata
include	matrix of included data
idx	integer vector of rows from which sampling is allowed
factors	boolean factor flag
i_fact	indices of factors in xA
nsample	number of samples
cost_mode	bool cost flag
iter	number of iterations
wCont	continuous weight
wFact	factor weights
wCorr	correlation weights
etaMat	eta matrix - either all 1, or user input
temperature	initial temperature
tdecrease	temperature decrease every length_cycle iterations
length_cycle	number of iterations between temperature decrease

Value

list with sampled data, indices, objective values, cost value, and final continuous weights for each sample

clhs documentation built on Oct. 14, 2021, 9:06 a.m.