CVX‐based algorithms for constructing various optimal regression designs

DOI10.1002/cjs.11499OpenAlexW2943137452WikidataQ127930425 ScholiaQ127930425MaRDI QIDQ5107592

Julie Zhou, Weng Kee Wong

Publication date: 28 April 2020

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://escholarship.org/uc/item/3kh4w4p4

zbMATH Keywords

convex optimizationsemi-definite programmingequivalence theoremdose-response modelmulti-objective designmulti-stage design

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (5)

R-optimal designs for multi-response regression models with multi-factors ⋮ Minimax A‐, c‐, and I‐optimal regression designs for models with heteroscedastic errors ⋮ Minimax D-optimal designs for multivariate regression models with multi-factors ⋮ Using CVX to Construct Optimal Designs for Biomedical Studies with Multiple Objectives ⋮ Constructing K-optimal designs for regression models

Uses Software

• Matlab

This page was built for publication: CVX‐based algorithms for constructing various optimal regression designs