distr.optim: To implement the Dynamic Programming (DP) solution procedure...

In stratifyR: Optimal Stratification of Univariate Populations

To implement the Dynamic Programming (DP) solution procedure on the stratification problem presented in the form of a Mathematical Programming Problem (MPP)

Description

This function uses the Dynamic Programming (DP) solution procedure in solving the objective function for the univariate stratification problem. It calculates the objective function values using the brute-force algorithm and stores those values in the matrices and keeps a copy in my_env so that a global minimum could be obtained.

Usage

distr.optim(k, n, incf, minYk, maxYk, isFirstRun = TRUE, my_env)

Arguments

k	A numeric: number of strata
n	A numeric: is the distance*1000
incf	A numeric: 10e-3 when k=1 and 10e-5 for k>=2
minYk	A numeric: index to access minimum elements in the matrix
maxYk	A numeric: index to access maximum elements in the matrix
isFirstRun	A boolean: TRUE/FALSE parameter
my_env	My environment my_env has various constants and calculations stored from earlier opeartions through various other functions

Value

returns the array filled with calculations of objective function values

Author(s)

Karuna Reddy <[e-mail]>
MGM Khan <[e-mail]>

stratifyR documentation built on April 3, 2025, 7:32 p.m.