Inference and testing for structural change in general Poisson autoregressive models

DOI10.1214/15-EJS1038zbMath1349.62397arXiv1305.1751MaRDI QIDQ491391

Paul Doukhan, William Charky Kengne

Publication date: 25 August 2015

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

Full work available at URL: https://arxiv.org/abs/1305.1751

zbMATH Keywords

consistencyasymptotic normalitytime seriesmaximum likelihood estimatorlimit distributionchange-pointPoisson autoregressionsemiparametric test

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03) Central limit and other weak theorems (60F05) Point estimation (62F10) Asymptotic properties of parametric tests (62F05)

Related Items

Poisson QMLE for change-point detection in general integer-valued time series models, Piecewise autoregression for general integer-valued time series, Test for Conditional Variance of Integer-Valued Time Series, A robust approach for testing parameter change in Poisson autoregressive models, Test of parameter changes in a class of observation-driven models for count time series, Consistent model selection procedure for general integer-valued time series, A general procedure for change-point detection in multivariate time series, Asymptotic normality and parameter change test for bivariate Poisson INGARCH models, Threshold negative binomial autoregressive model, Conditional maximum likelihood estimation for a class of observation-driven time series models for count data, Robust estimation for general integer-valued time series models, Score test for parameter change in Poisson autoregressive models, Mixtures of Nonlinear Poisson Autoregressions, Inference for nonstationary time series of counts with application to change-point problems

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Modelling time series of counts with overdispersion
• On weak dependence conditions for Poisson autoregressions
• Absolute regularity and ergodicity of Poisson count processes
• Maximum likelihood estimation for an observation driven model for Poisson counts
• Asymptotic normality of the quasi-maximum likelihood estimator for multidimensional causal processes
• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
• Weakly dependent chains with infinite memory
• Weighted empirical and quantile processes
• Nonlinear Poisson autoregression
• Some recent theory for autoregressive count time series
• Multiple breaks detection in general causal time series using penalized quasi-likelihood
• A goodness-of-fit test for Poisson count processes
• Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator
• Ergodicity of the 2D Navier-Stokes equations with degenerate stochastic forcing
• On discriminating between long-range dependence and changes in mean
• Theory and inference for a class of nonlinear models with application to time series of counts
• Poisson Autoregression
• Parameter change test for random coefficient integer-valued autoregressive processes with application to polio data analysis
• A negative binomial model for time series of counts
• A statistical framework for the analysis of multivariate infectious disease surveillance counts
• Integer-Valued GARCH Process
• Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
• Use of Cumulative Sums of Squares for Retrospective Detection of Changes of Variance
• K-Sample Analogues of the Kolmogorov-Smirnov and Cramer-V. Mises Tests
• Interventions in INGARCH processes
• Changepoints in times series of counts
• An Inequality and Almost Sure Convergence
• Threshold heteroskedastic models