Optimal designs for additive mixture model with heteroscedastic errors

Fei Yan, Chongqi Zhang*, Heng Peng

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)

Abstract

This paper presents a study of D- and A-optimality of direct sum designs for additive mixture models when the errors are heteroscedastic. Sufficient conditions are given so that D- and A-optimal designs for additive mixture models can be constructed from the D- and A-optimal designs for homogeneous models in sub-mixture systems.

Original languageEnglish
Pages (from-to)6401-6411
Number of pages11
JournalCommunications in Statistics - Theory and Methods
Volume46
Issue number13
Early online date2 Mar 2017
DOIs
Publication statusPublished - 3 Jul 2017

Scopus Subject Areas

  • Statistics and Probability

User-Defined Keywords

  • A-optimality
  • additive mixture models
  • D-optimality
  • direct sum design
  • heteroscedasticity
  • mixture experiments

Fingerprint

Dive into the research topics of 'Optimal designs for additive mixture model with heteroscedastic errors'. Together they form a unique fingerprint.

Cite this