Hidden semi-Markov-switching quantile regression for time series (Q830112)

scientific article; zbMATH DE number 7345465

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English	Hidden semi-Markov-switching quantile regression for time series	scientific article; zbMATH DE number 7345465

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instance of

scholarly article

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title

Hidden semi-Markov-switching quantile regression for time series (English)

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Computational Statistics and Data Analysis

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publication date

7 May 2021

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zbMATH Keywords

asymmetric Laplace distribution

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Markov-switching models

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sojourn distribution

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quantile regression

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EM algorithm

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maximum likelihood estimation

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describes a project that uses

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full work available at URL

https://doi.org/10.1016/j.csda.2021.107208

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cites work

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A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains

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The mixture transition distribution model for high-order Markov chains and non-Gaussian time series

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Bayesian quantile regression using the skew exponential power distribution

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Stylized facts of financial time series and hidden semi-Markov models

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The influence of initial conditions on maximum likelihood estimation of the parameters of a binary hidden Markov model

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

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Parametric modeling of quantile regression coefficient functions

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Quantile regression for longitudinal data using the asymmetric Laplace distribution

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A Markov-switching generalized additive model for compound Poisson processes, with applications to operational loss models

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Handbook of Spatial Epidemiology

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An Introduction to the Application of the Theory of Probabilistic Functions of a Markov Process to Automatic Speech Recognition

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Markov-switching quantile autoregression: a Gibbs sampling approach

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Numerical Maximisation of Likelihood: A Neglected Alternative to EM?

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Time Series Clustering and Classification

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Latent drop-out based transitions in linear quantile hidden Markov models for longitudinal responses with attrition

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Linear quantile regression models for longitudinal experiments: an overview

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Finite mixture models

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Modeling loss data using mixtures of distributions

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Multivariate Receptor Modeling for Temporally Correlated Data by Using MCMC

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Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress

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Selecting the number of states in hidden Markov models: pragmatic solutions illustrated using animal movement

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Compound unimodal distributions for insurance losses

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Generalized Additive Models for Location, Scale and Shape

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EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective

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Fitting hidden semi-Markov models to breakpoint rainfall data

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GAMLSS: A distributional regression approach

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Quantile regression: A short story on how and why

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Mixtures of quantile regressions

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Quantile cointegrating regression

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Markov regime-switching quantile regression models and financial contagion detection

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Bayesian quantile regression

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Hidden Markov models for time series. An introduction using R

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Identifiers

Mathematics Subject Classification ID

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10.1016/J.CSDA.2021.107208

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Sitelinks

Mathematics(1 entry)

mardi Publication:830112