Simplified partially observed quasi-information matrix

Thuan Nguyen; Jiming Jiang

doi:10.1007/s00180-022-01221-8

Simplified partially observed quasi-information matrix

Thuan Nguyen, Jiming Jiang

School Of Public Health

Research output: Contribution to journal › Article › peer-review

Abstract

We propose a simplified version of the partially observed quasi-information matrix (Poquim) method for inference about non-Gaussian linear mixed models and show its computational advantage over the original method. We illustrate the difference, and compare performance of the simplified version with Poquim as well as the normality-based method in simulation studies. An example of real-data analysis is considered.

Original language	English (US)
Pages (from-to)	171-189
Number of pages	19
Journal	Computational Statistics
Volume	38
Issue number	1
DOIs	https://doi.org/10.1007/s00180-022-01221-8
State	Published - Mar 2023

Keywords

Asymptotic covariance matrix
Fisher information
Non-Gaussian linear mixed model
Quasi-likelihood
REML
Spoquim

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Computational Mathematics

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10.1007/s00180-022-01221-8

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AB - We propose a simplified version of the partially observed quasi-information matrix (Poquim) method for inference about non-Gaussian linear mixed models and show its computational advantage over the original method. We illustrate the difference, and compare performance of the simplified version with Poquim as well as the normality-based method in simulation studies. An example of real-data analysis is considered.

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KW - Quasi-likelihood

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Simplified partially observed quasi-information matrix

Abstract

Keywords

ASJC Scopus subject areas

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