A robust linear mixed-effects model for longitudinal data using an innovative multivariate skew-Huber distribution
DOI10.1016/j.jmva.2021.104856zbMath1480.62101OpenAlexW3210657768MaRDI QIDQ2057843
Iraj Kazemi, Raziyeh Mohammadi
Publication date: 7 December 2021
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmva.2021.104856
outliersheterogeneity effectsmodified Cholesky decompositiontuning parametervariance-covariance structures
Inference from spatial processes (62M30) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10)
Uses Software
Cites Work
- Understanding predictive information criteria for Bayesian models
- Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective
- Robustness of the linear mixed model to misspecified error distribution
- Linear mixed models with skew-elliptical distributions: a Bayesian approach
- Robust linear mixed models for small area estimation
- Scale and shape mixtures of multivariate skew-normal distributions
- Smoothing and mixed models
- Robust designs for generalized linear mixed models with possible model misspecification
- Mixed Models
- Smoothing Splines
- Robust linear mixed models using the skew t distribution with application to schizophrenia data
- Random Effects Selection in Linear Mixed Models
- Sampling-Based Approaches to Calculating Marginal Densities
- Cholesky Decompositions and Estimation of A Covariance Matrix: Orthogonality of Variance Correlation Parameters
- A new class of multivariate skew distributions with applications to bayesian regression models
- Robust Linear Mixed Models with Normal/Independent Distributions and Bayesian MCMC Implementation
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