Estimation of patterned covariance in the multivariate linear models: an outer product least-squares approach

DOI10.1080/02331888.2014.913046zbMath1396.62104OpenAlexW1974262019MaRDI QIDQ5263987

Xiaoqian Liu, Jian-Hua Hu

Publication date: 20 July 2015

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2014.913046

zbMATH Keywords

estimationleast squaresmultivariate linear modelouter product least squarespatterned covarianceuniform correlationgeneral \(q\)-dependence

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12)

Related Items

Multiple-response repeated measurement or multivariate growth curve model with distribution-free errors

Cites Work

• Estimation of parameters in the growth curve model via an outer product least squares approach for covariance
• Estimation of parameters in a generalized GMANOVA model based on an outer product analogy and least squares
• Explicit estimators under \(m\)-dependence for a multivariate normal distribution
• A trace inequality of John von Neumann
• Restricted expected multivariate least squares
• The non-singularity of generalized sample covariance matrices
• Testing some covariance structures under a growth curve model
• Linear Models in a general parametric form
• IV.—On Least Squares and Linear Combination of Observations
• On the Expressions of Estimability in Testing General Linear Hypotheses
• Linear Least Squares Regression
• Testing Compound Symmetry in a Normal Multivariate Distribution
• Sample Criteria for Testing Equality of Means, Equality of Variances, and Equality of Covariances in a Normal Multivariate Distribution

This page was built for publication: Estimation of patterned covariance in the multivariate linear models: an outer product least-squares approach