Integer autoregressive models with structural breaks

DOI10.1080/02664763.2013.823920OpenAlexW2045834395MaRDI QIDQ5129143

Neelabh Rohan, T. V. Ramanathan, Akanksha S. Kashikar

Publication date: 26 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.823920

zbMATH Keywords

Gibbs samplingINAR modelsstructural break MCMC

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (10)

Piecewise autoregression for general integer-valued time series ⋮ Statistical analysis of the non-stationary binomial AR(1) model with change point ⋮ Forecasting overdispersed INAR(1) count time series with negative binomial marginal ⋮ Efficient estimation in semiparametric self-exciting threshold INAR processes ⋮ Testing the constancy of the thinning parameter in a random coefficient integer autoregressive model ⋮ Self-exciting threshold -valued autoregressive processes for non-stationary time series of counts ⋮ Estimation of parameters in the self-exciting threshold autoregressive processes for nonlinear time series of counts ⋮ Thinning-based models in the analysis of integer-valued time series: a review ⋮ On MCMC sampling in self-exciting integer-valued threshold time series models ⋮ Generalized Poisson integer-valued autoregressive processes with structural changes

Cites Work

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• Heterogeneous INAR(1) model with application to car insurance
• Integer valued AR processes with explanatory variables
• Calculating posterior distributions and modal estimates in Markov mixture models
• Estimation and comparison of multiple change-point models
• Estimation and information in stationary time series
• Asymmetric Volatility Models with Structural Breaks
• Inference for pth-order random coefficient integer-valued autoregressive processes
• Analysing State Dependences in Emotional Experiences by Dynamic Count Data Models
• An integer-valued pth-order autoregressive structure (INAR(p)) process
• Regression and time series model selection in small samples
• Analysis of low count time series data by poisson autoregression
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
• Change Detection in INAR(p) Processes Against Various Alternative Hypotheses
• Changepoints in times series of counts
• MCMC for Integer-Valued ARMA processes
• Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.

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