PingYangChen/DiscrimOD: DiscrimOD: Finding Optimal Discrimination Designs by Hybridizing Particle Swarm and L-BFGS Algorithms
Version 0.1.1

The **DiscrimOD** package adopts a hybrid algorithm to search for the optimal discrimination designs when there are two or more than two competing models under normal or non-normal error assumption. This hybrid algorithm is chosen to efficiently solve the maximin design criteria in the optimal discrimination design problem which is usually a challenging task. It combines the particle swarm optimization (PSO) algorithm and the L-BFGS algorithm to tackle the outer and inner objectives of the maximin design criterion, respectively. The equivalence theorems for various discrimination criteria are also available for verifying the optimal discrimination designs.

Getting started

Package details

AuthorPing-Yang Chen [aut, cre]
MaintainerPing-Yang Chen <[email protected]>
LicenseMIT + file LICENSE
Version0.1.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("PingYangChen/DiscrimOD")
PingYangChen/DiscrimOD documentation built on Aug. 25, 2018, 8:22 p.m.