Quantile regression for longitudinal data based on latent Markov subject-specific parameters

DOI10.1007/s11222-010-9213-0zbMath1322.62206OpenAlexW2086020235WikidataQ59397009 ScholiaQ59397009MaRDI QIDQ746190

Alessio Farcomeni

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-010-9213-0

zbMATH Keywords

longitudinal datahidden Markov modelquantile regressionasymmetric Laplace distribution

Mathematics Subject Classification ID

Order statistics; empirical distribution functions (62G30) General nonlinear regression (62J02) Markov processes: estimation; hidden Markov models (62M05)

Related Items (28)

Weighted quantile regression for longitudinal data using empirical likelihood ⋮ Quantile regression modeling of latent trajectory features with longitudinal data ⋮ Hidden semi-Markov-switching quantile regression for time series ⋮ Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates ⋮ Marginal M-quantile regression for multivariate dependent data ⋮ Generalized Linear Mixed Models Based on Latent Markov Heterogeneity Structures ⋮ Model-based time-varying clustering of multivariate longitudinal data with covariates and outliers ⋮ Quantile hidden semi-Markov models for multivariate time series ⋮ Likelihood-based quantile mixed effects models for longitudinal data with multiple features via MCEM algorithm ⋮ Smoothed quantile regression with nonignorable dropouts ⋮ Modelling and estimation of nonlinear quantile regression with clustered data ⋮ Latent drop-out based transitions in linear quantile hidden Markov models for longitudinal responses with attrition ⋮ Markov-switching quantile autoregression: a Gibbs sampling approach ⋮ Brq: an R package for Bayesian quantile regression ⋮ Linear quantile regression models for longitudinal experiments: an overview ⋮ Smooth expectiles for panel data using penalized splines ⋮ Finite mixtures of quantile and M-quantile regression models ⋮ Quantile regression for longitudinal data with a working correlation model ⋮ Linear quantile mixed models ⋮ Parsimonious Hidden Markov Models for Matrix-Variate Longitudinal Data ⋮ Information matrix for hidden Markov models with covariates ⋮ Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates ⋮ S-estimation of hidden Markov models ⋮ A gradient search maximization algorithm for the asymmetric Laplace likelihood ⋮ Quantile regression-based Bayesian semiparametric mixed-effects models for longitudinal data with non-normal, missing and mismeasured covariate ⋮ Quantile regression-based Bayesian joint modeling analysis of longitudinal-survival data, with application to an AIDS cohort study ⋮ Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data ⋮ Weighted quantile regression for longitudinal data

Uses Software

• R

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