Estimating the Variance of Estimator of the Latent Factor Linear Mixed Model Using Supplemented Expectation-Maximization Algorithm

This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as linear mixed models for longitudinal data. The latent factor linear mixed model (LFLMM) is a method generally used for analysing changes in high-dimensional longitudinal data. It is usual that the mod...

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Bibliographic Details

Published in:	Symmetry (Basel) Vol. 13; no. 7; p. 1286
Main Authors:	Angraini, Yenni, Notodiputro, Khairil Anwar, Folmer, Henk, Saefuddin, Asep, Toharudin, Toni
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.07.2021
Subjects:	Algorithms Dimensional changes Estimates Mathematical models Matrices (mathematics) Maximization Normal distribution Optimization Regression coefficients Simulation Statistical analysis Variables Variance
ISSN:	2073-8994, 2073-8994
Online Access:	Get full text
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