Estimation of parameters in the growth curve model via an outer product least squares approach for covariance

DOI10.1016/j.jmva.2012.02.007zbMath1238.62066OpenAlexW1987648679MaRDI QIDQ414550

S. Ejaz Ahmed, Fuxiang Liu, Jian-Hua Hu

Publication date: 11 May 2012

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2012.02.007

zbMATH Keywords

COPLS estimatortwo-stage generalized least squares

Mathematics Subject Classification ID

Related Items (7)

Model determination and estimation for the growth curve model via group SCAD penalty ⋮ Estimation of parameters in a generalized GMANOVA model based on an outer product analogy and least squares ⋮ Multiple-response repeated measurement or multivariate growth curve model with distribution-free errors ⋮ Short-Time Linear Quadratic Form Technique for Estimating Fast-Varying Parameters in Feedback Loops ⋮ On intraclass structure estimation in the growth curve model ⋮ Estimation of parameters in the extended growth curve model via outer product least squares for covariance ⋮ Estimation of patterned covariance in the multivariate linear models: an outer product least-squares approach

Cites Work

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• Maximum likelihood estimators in multivariate linear normal models
• The simultaneous estimation of \(\text{tr} (D'B)+ \text{tr} (C\Sigma)\) in the growth curve model
• Singular Wishart and multivariate beta distributions
• Prediction of future observations in growth curve models. With discussion and a reply by the author
• Wishartness and independence of matrix quadratic forms in a normal random matrix
• A note on a Manova model applied to problems in growth curve
• Prediction and Estimation of Growth Curves With Special Covariance Structures
• The Effect of Covariance Structure on Variance Estimation in Balanced Growth-Curve Models with Random Parameters
• Multivariate Repeated-Measurement or Growth Curve Models with Multivariate Random-Effects Covariance Structure
• Minqe(U, I) and Umvique of the Covariance Matrix in the Growth Curve Model
• Bayesian inference for variance components using only error contrasts
• Testing Statistical Hypotheses
• A generalized multivariate analysis of variance model useful especially for growth curve problems
• The theory of least squares when the parameters are stochastic and its application to the analysis of growth curves
• Recovery of inter-block information when block sizes are unequal
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