Gram–Schmidt–Fisher scoring algorithm for parameter orthogonalization in MLE

DOI10.1080/23311835.2016.1159847zbMath1426.62084OpenAlexW2306967400MaRDI QIDQ4966746

Victor Apprey, John Kwagyan, George E. Bonney

Publication date: 27 June 2019

Published in: Cogent Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/23311835.2016.1159847

zbMATH Keywords

maximum likelihood estimationGram-Schmidt orthogonalizationcorrelated dataFisher scoring algorithmorthogonal parameters

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)

Uses Software

• CORRDAT
• MULTIMAX

Cites Work

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• Longitudinal data analysis using generalized linear models
• An extension of quasi-likelihood estimation
• Differential geometry of curved exponential families. Curvatures and information loss
• Differential-geometrical methods in statistics
• Correlated Binary Regression with Covariates Specific to Each Binary Observation
• Gram-Schmidt Orthogonalization of Multinormal Variates: Applications in Genetics
• On parameter orthogonality to the mean
• On the stability of maximum‐likelihood estimators of orthogonal parameters

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