Skew-Normal-Cauchy Linear Mixed Models

F. Kahrari (), C. S. Ferreira and R. B. Arellano-Valle
Additional contact information
F. Kahrari: Shahid Chamran University of Ahvaz
C. S. Ferreira: Federal University of Juiz de Fora
R. B. Arellano-Valle: Pontificia Universidad Católica de Chile

Sankhya B: The Indian Journal of Statistics, 2019, vol. 81, issue 2, No 1, 185-202

Abstract: Abstract In this work, a flexible class of linear mixed models is introduced by assuming that the random effects and model errors follow a skew-normal-Cauchy distribution. The likelihood function and the information matrix based on of the observed data are computed. An EM-type algorithm is also proposed for estimating the parameters that seems to provide some advantages over a direct maximization of the likelihood function. Finally, the performance of the proposed model is evaluated numerically from simulated an real data.

Keywords: EM-algorithm; Shape mixture; Skew-normal-cauchy distribution; Mixed effects model; Primary 62H10; Secondary 62F99; 62E99 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13571-018-0173-2

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