Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/32460

Title: Maximum Likelihood and L2 Environmental Indices in Joint Regression Analysis
Authors: Pereira, Dulce G.
Editors: Mejza, Stanisław
Kozłowska, Maria
Keywords: Joint Regression Analysis
Maximum likelihood estimators
Likelihood ratio tests
L2 environmental indices
Issue Date: 30-Jun-2022
Publisher: Sciendo
Citation: Pereira,D.G.(2022). Maximum Likelihood and L2 Environmental Indices in Joint Regression Analysis. Biometrical Letters,59(1) 23-46. https://doi.org/10.2478/bile-2022-0003
Abstract: This paper describes an iterative analysis of incomplete genotype  environment data. L2 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.
URI: https://www.sciendo.com/article/10.2478/bile-2022-0003
http://hdl.handle.net/10174/32460
Type: article
Appears in Collections:CIMA - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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