Robust modeling of multivariate longitudinal data using modified Cholesky and hypersphere decompositions-Reference-Cited by-同舟云学术

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Robust modeling of multivariate longitudinal data using modified Cholesky and hypersphere decompositions

Published:2022-06 Issue: Volume:170 Page:107439
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Rhee Anbin,Kwak Min-Sun,Lee Keunbaik

Funder

Ministry of Education, Science and Technology

National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference24 articles.

1. Asymptotically efficient estimation of covariance matrices with linear structure;Anderson;Ann. Stat.,1973

2. The matrixlogarithm covariance matrix;Chiu;J. Am. Stat. Assoc.,1996

3. A new nested cholesky decomposition and estimation for the covariance matrix of bivariate longitudinal data;Feng;Comput. Stat. Data Anal.,2016

4. Longitudinal data analysis using t-type regression;He;J. Stat. Plan. Inference,2004

5. Unconstrained models for the covariance structure of multivariate longitudinal data;Kim;J. Multivar. Anal.,2012

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1. A general robust approach for joint modeling of the family of scale mixture of Normal distribution;Signal Processing;2024-07

2. Multivariate probit linear mixed models for multivariate longitudinal binary data;Statistics in Medicine;2024-02-06

3. A General Robust Approach for Joint Modeling of the Family of Scale Mixture of Normal Distribution;2023

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