New Algorithms for Evaluating the Log-Likelihood Function Derivatives in the AI-REML Method

DOI10.1080/03610910902912944zbMath1167.62090OpenAlexW2091543501MaRDI QIDQ3391875

Kateryna Mishchenko, Maya G. Neytcheva

Publication date: 13 August 2009

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610910902912944

zbMATH Keywords

spectral decompositionvariance component estimationWoodbury's formulaidentity-by-descent (IBD) matrixreduced computational complexityrestricted maximum likelihood algorithm (REML)

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Genetics and epigenetics (92D10) Complexity and performance of numerical algorithms (65Y20)

Related Items (1)

Assessing a multiple QTL search using the variance component model

Cites Work

• Some new algorithms for computing restricted maximum likelihood estimates of variance components
• Average Information REML: An Efficient Algorithm for Variance Parameter Estimation in Linear Mixed Models

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