Premium
Optimal balanced block designs for correlated observations
Author(s) -
Khodsiani Razieh,
Pooladsaz Saeid
Publication year - 2020
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.11549
Subject(s) - correlation , block (permutation group theory) , binary number , mathematics , value (mathematics) , optimal design , constant (computer programming) , construct (python library) , block size , statistics , mathematical optimization , computer science , algorithm , combinatorics , arithmetic , geometry , programming language , computer security , key (lock)
The construction of universally optimal designs, if such exist, is difficult to obtain, especially when there are some nuisance effects or correlated errors. The hub correlation is a special correlation structure with applications to experiments in genetics, networks and other areas in industry and agriculture. There may be restrictions on the correlation values of the hub structure depending on the experiment. Optimality of block designs under hub correlation has been studied for the case of a constant correlation value. In this article, we consider the hub structure when one of the correlation values is different from the others, and the universally optimal block designs, binary or non‐binary, are theoretically obtained. Also, we introduce an algorithm to construct the optimal designs. The Canadian Journal of Statistics 48: 596–604; 2020 © 2020 Statistical Society of Canada