Testing for parameter constancy in non-Gaussian time series

DOI10.1111/j.1467-9892.2012.00810.xzbMath1274.62592OpenAlexW1571483568MaRDI QIDQ2852478

Lu Han, B. P. M. McCabe

Publication date: 9 October 2013

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.2012.00810.x

zbMATH Keywords

CUSUM testnon-Gaussian time seriesdiscrete valued count time seriessup-test

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Numerical analysis or methods applied to Markov chains (65C40) Non-Markovian processes: hypothesis testing (62M07)

Related Items (3)

A new minification integer‐valued autoregressive process driven by explanatory variables ⋮ Testing the constancy of the thinning parameter in a random coefficient integer autoregressive model ⋮ Bayesian Outlier Detection in Non‐Gaussian Autoregressive Time Series

Cites Work

• Estimation in nonlinear time series models
• On conditional least squares estimation for stochastic processes
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• Efficient Estimation of Auto-Regression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models
• Tests for Parameter Instability and Structural Change With Unknown Change Point
• Approximation Theorems of Mathematical Statistics
• Stochastic Limit Theory
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Theory & Methods: Non‐Gaussian Conditional Linear AR(1) Models
• Analysis of low count time series data by poisson autoregression
• FIRST-ORDER INTEGER-VALUED AUTOREGRESSIVE (INAR(1)) PROCESS
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