Statistical Synthesis of Heckman-Based Selection with Conway-Maxwell-Poisson Probability Models

This research elucidates the theoretical derivation and statistical foundations of the integrated HeckCOMPoisson model, which synthesizes the Heckman selection framework with the Conway-Maxwell-Poisson probability distribution. This unified statistical approach was formulated specifically to address truncated count data subject to sample selection mechanisms. The model exhibits superior statistical properties across multiple evaluation criteria: it demonstrates excellent performance in parametric Goodness-of-Fit assessments, yields consistent maximum likelihood estimates for count data with selection bias, and efficiently parameterizes both under-dispersed and over-dispersed count distributions. A distinguishing characteristic of the HeckCOMPoisson distribution is its parametric flexibility and its robust estimation properties when modeling discrete count data with heterogeneous dispersion parameters.

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Publication Details

Journal
Asian Journal of Probability and Statistics
Published
2025-02-26
DOI
https://doi.org/10.9734/ajpas/2025/v27i3728
Primary Topic
Advanced Statistical Process Monitoring
Type
article
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article

Statistical Synthesis of Heckman-Based Selection with Conway-Maxwell-Poisson Probability Models

Leonard King’ora Thuo
Asian Journal of Probability and Statistics
Advanced Statistical Process Monitoring
article

Statistical Synthesis of Heckman-Based Selection with Conway-Maxwell-Poisson Probability Models

Leonard King’ora Thuo
article en

Abstract

This research elucidates the theoretical derivation and statistical foundations of the integrated HeckCOMPoisson model, which synthesizes the Heckman selection framework with the Conway-Maxwell-Poisson probability distribution. This unified statistical approach was formulated specifically to address truncated count data subject to sample selection mechanisms. The model exhibits superior statistical properties across multiple evaluation criteria: it demonstrates excellent performance in parametric Goodness-of-Fit assessments, yields consistent maximum likelihood estimates for count data with selection bias, and efficiently parameterizes both under-dispersed and over-dispersed count distributions. A distinguishing characteristic of the HeckCOMPoisson distribution is its parametric flexibility and its robust estimation properties when modeling discrete count data with heterogeneous dispersion parameters.

Asian Journal of Probability and StatisticsVol. 27(3)
Kibabii University (KE)
Openalex Percentile: Top 96%
Advanced Statistical Process Monitoring
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