Poisson count time series

This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced. Modeling nonstationary series with covariates motivates consideration of methods where the Poisson parameter depends on time. Here, estimation methods are developed for some of the more flexible methods. The results are used in the analysis of (1) a count sequence of tropical cyclones occurring in the North Atlantic Basin since 1970, and (2) the number of no‐hitter games pitched in Major League Baseball since 1893. Tests for whether the Poisson marginal distribution is appropriate are included.

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Publication Details

Journal
Journal of Time Series Analysis
Published
2024-11-29
DOI
https://doi.org/10.1111/jtsa.12799
Citations
3
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
1.62

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article

Poisson count time series

Robert Lund, Jiajie Kong
3 citations
Journal of Time Series Analysis
Financial Risk and Volatility Modeling
1.62
article

Poisson count time series

Robert Lund, Jiajie Kong
article en
3 citations

Abstract

This article reviews and compares popular methods, some old and some recent, that produce time series having Poisson marginal distributions. The article begins by narrating ways where time series with Poisson marginal distributions can be produced. Modeling nonstationary series with covariates motivates consideration of methods where the Poisson parameter depends on time. Here, estimation methods are developed for some of the more flexible methods. The results are used in the analysis of (1) a count sequence of tropical cyclones occurring in the North Atlantic Basin since 1970, and (2) the number of no‐hitter games pitched in Major League Baseball since 1893. Tests for whether the Poisson marginal distribution is appropriate are included.

Journal of Time Series AnalysisVol. 47(2)
University of California, Santa Cruz (US)
National Science Foundation
Life below water
Openalex Percentile: Top 14%
Financial Risk and Volatility Modeling
1.62
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Poisson count time series — Robert Lund, Jiajie Kong · Journal of Time Series Analysis (2024) | TGRS Research Map | TGRS