Maximum Likelihood and L<sub>2</sub> Environmental Indices in Joint Regression Analysis-Reference-Cited by-同舟云学术

Maximum Likelihood and L₂ Environmental Indices in Joint Regression Analysis

Published:2022-06-01 Issue:1 Volume:59 Page:23-46
ISSN:2199-577X
Container-title:Biometrical Letters
language:en
Short-container-title:

Author:

Pereira Dulce Gamito¹

Affiliation:

1. Departamento de Matemática , Escola de Ciências e Tecnologia, Centro de Investigação em Matemática e Aplicações, Instituto de Investigação e Formação Avançada , Universidade de Évora , Rua Romão Ramalho 59 , Évora , Portugal

Abstract

Summary This paper describes an iterative analysis of incomplete genotype × environment data. L 2 environmental indices were introduced to enable the use of Joint Regression Analysis (JRA) in analyzing experiments with incomplete blocks. We now show how, once normality of yields is assumed, the introduction of L2 environmental indices provides a theoretical framework for Joint Regression Analysis. Using this framework, maximum likelihood estimators are obtained and likelihood ratio tests are derived. It is noted that the technique allows unequal weighting of data, and the special case of complete blocks is discussed.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/bile-2022-0003

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