Algorithmic Construction of Bayesian Optimal Block Designs Using the Linear Mixed Effects Model

Dibaba B. Gemechu, Legesse K. Debusho and Linda M. Haine

International Journal of Statistics and Probability, 2025, vol. 14, issue 1, 50

Abstract: In this paper a numerical method for construction of optimal Bayesian block designs of size two is considered. The main focus is on implementing prior information on the unknown error variance and variance of random block effects to calculate the A- and D-optimal designs. It is noted from the numerical results that the A- and D-optimal Bayesian block designs are insensitive to the shape of the prior distributions.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ccsenet.org/journal/index.php/ijsp/article/download/0/0/51519/56011 (application/pdf)
https://ccsenet.org/journal/index.php/ijsp/article/view/0/51519 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:ijspjl:v:14:y:2025:i:1:p:50

Access Statistics for this article

More articles in International Journal of Statistics and Probability from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().