Tests for Changes in Count Time Series Models With Exogenous Covariates

ABSTRACT We deal with a parametric change in models for count time series with exogenous covariates specified via the conditional distribution, i.e., with integer generalized autoregressive conditional heteroscedastic models with covariates (INGARCH‐X). CUSUM‐type methods for the change point detection are proposed, and their asymptotic distributions are derived. The finite‐sample behavior of the proposed tests is illustrated through a Monte Carlo simulation study and on a real‐time series of daily traffic accident counts.

Authors

Institutions

Publication Details

Journal
Journal of Time Series Analysis
Published
2025-04-20
DOI
https://doi.org/10.1111/jtsa.12830
Citations
1
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
Field-Weighted Citation Impact
2.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Tests for Changes in Count Time Series Models With Exogenous Covariates

Šárka Hudecová, Marie Hušková
1 citations
Journal of Time Series Analysis
Statistical Methods and Bayesian Inference
2.63
article

Tests for Changes in Count Time Series Models With Exogenous Covariates

Šárka Hudecová, Marie Hušková
article en
1 citations

Abstract

ABSTRACT We deal with a parametric change in models for count time series with exogenous covariates specified via the conditional distribution, i.e., with integer generalized autoregressive conditional heteroscedastic models with covariates (INGARCH‐X). CUSUM‐type methods for the change point detection are proposed, and their asymptotic distributions are derived. The finite‐sample behavior of the proposed tests is illustrated through a Monte Carlo simulation study and on a real‐time series of daily traffic accident counts.

Journal of Time Series Analysis
Charles University (CZ)
Grantová Agentura České Republiky
Openalex Percentile: Top 12%
Statistical Methods and Bayesian Inference
2.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.