On MCMC sampling in self-exciting integer-valued threshold time series models

DOI10.1016/j.csda.2021.107410OpenAlexW4200144792MaRDI QIDQ2076110

Qingqing Zhang, Kai Yang, Xiaogang Dong, Xinyang Yu

Publication date: 18 February 2022

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2021.107410

zbMATH Keywords

latent variablesBayesian inferenceMCMC samplingthreshold autoregressive modelinteger-valued time series

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (7)

On bivariate threshold Poisson integer-valued autoregressive processes ⋮ Bayesian inference for a mixture double autoregressive model ⋮ Asymptotic inference for moderate deviations from a unit root of nearly unstable INAR(1) processes ⋮ First-order binomial autoregressive processes with Markov-switching coefficients ⋮ A nonparametric Bayesian analysis for meningococcal disease counts based on integer-valued threshold time series models ⋮ A novel multivariable grey prediction model with different accumulation orders and performance comparison ⋮ Generalized autoregressive score models based on sinh-arcsinh distributions for time series analysis

Uses Software

• Bolstad

Cites Work

• Unnamed Item
• Unnamed Item
• Exact and approximate Bayesian inference for low integer-valued time series models with intractable likelihoods
• Markov chains and stochastic stability
• Bayesian estimation of the Gaussian mixture GARCH model
• Discrete analogues of self-decomposability and stability
• Self-exciting threshold binomial autoregressive processes
• Compound Poisson INAR(1) processes: stochastic properties and testing for overdispersion
• True integer value time series
• Poisson-Lindley INAR(1) model with applications
• Bayesian nonparametric forecasting for INAR models
• Generalized Poisson autoregressive models for time series of counts
• Quasi-likelihood inference for self-exciting threshold integer-valued autoregressive processes
• Inference from iterative simulation using multiple sequences
• An integer-valued threshold autoregressive process based on negative binomial thinning
• Random coefficients integer-valued threshold autoregressive processes driven by logistic regression
• Deviance information criterion for latent variable models and misspecified models
• Estimation of parameters in the self-exciting threshold autoregressive processes for nonlinear time series of counts
• First-order random coefficients integer-valued threshold autoregressive processes
• Bayesian estimation of an autoregressive model using Markov chain Monte Carlo
• Integer-Valued Self-Exciting Threshold Autoregressive Processes
• Efficient Estimation of Auto-Regression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models
• THE INTEGER-VALUED AUTOREGRESSIVE (INAR(p)) MODEL
• An integer-valued pth-order autoregressive structure (INAR(p)) process
• GENERALIZED INTEGER-VALUED AUTOREGRESSION
• Bayesian Measures of Model Complexity and Fit
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
• Threshold autoregression analysis for finite-range time series of counts with an application on measles data
• Thinning-based models in the analysis of integer-valued time series: a review
• Self-Excited Threshold Poisson Autoregression
• Estimation and testing for the integer-valued threshold autoregressive models based on negative binomial thinning
• Integer autoregressive models with structural breaks
• Introduction to Bayesian Statistics
• Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation
• MCMC for Integer-Valued ARMA processes
• The Deviance Information Criterion: 12 Years on
• Retrospective Bayesian outlier detection in INGARCH series
• Count Time Series: A Methodological Review

This page was built for publication: On MCMC sampling in self-exciting integer-valued threshold time series models