Structure Assessment in Count Time Series

Assessing the performance of an estimated model for count time series is critical for subsequent statistical inference and distributional forecasting. This article reviews the most commonly used count time series models and focuses on evaluating their goodness of fit. Various formal statistical tests are presented, along with useful graphical diagnostic tools. The methods are illustrated on a real data example.

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Publication Details

Journal
Annual Review of Statistics and Its Application
Published
2025-10-29
DOI
https://doi.org/10.1146/annurev-statistics-042424-114518
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Structure Assessment in Count Time Series

Šárka Hudecová
Annual Review of Statistics and Its Application
Financial Risk and Volatility Modeling
article

Structure Assessment in Count Time Series

Šárka Hudecová
article en

Abstract

Assessing the performance of an estimated model for count time series is critical for subsequent statistical inference and distributional forecasting. This article reviews the most commonly used count time series models and focuses on evaluating their goodness of fit. Various formal statistical tests are presented, along with useful graphical diagnostic tools. The methods are illustrated on a real data example.

Annual Review of Statistics and Its ApplicationVol. 13(1)
Charles University (CZ)
Openalex Percentile: Top 60%
Financial Risk and Volatility Modeling
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Structure Assessment in Count Time Series — Šárka Hudecová · Annual Review of Statistics and Its Application (2025) | TGRS Research Map | TGRS