Estimating Population Size of Criminals: A New Horvitz–Thompson Estimator under One-Inflated Positive Poisson–Lindley Model

Many crime datasets often display an excess of ?1? counts, arises when arrested criminals have the desire and ability to avoid subsequent arrests. In this study, a new Horvitz?Thompson (HT) estimator under one-inflated positive Poisson?Lindley (OIPPL) distribution which allow for one-inflation and t...

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Detalles Bibliográficos
Autor principal: Tajuddin, Razik Ridzuan Mohd (Autor)
Otros Autores: Ismail, Noriszura ; Ibrahim, Kamarulzaman
Tipo de documento: Electrónico Artículo
Lenguaje:Inglés
Publicado: 2022
En: Crime & delinquency
Año: 2022, Volumen: 68, Número: 6/7, Páginas: 1004-1034
Acceso en línea: Volltext (lizenzpflichtig)
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Palabras clave:
capture-recapture
inflated models
large number of ones
number of criminals
zero-truncated Poisson–Lindley
Descripción
Sumario:Many crime datasets often display an excess of ?1? counts, arises when arrested criminals have the desire and ability to avoid subsequent arrests. In this study, a new Horvitz?Thompson (HT) estimator under one-inflated positive Poisson?Lindley (OIPPL) distribution which allow for one-inflation and the existence of heterogeneity in the data is developed to estimate the hidden population size of criminals. From the simulation study and applications to real crime datasets, the OIPPL is capable to provide an adequate fit to the datasets considered and the proposed HT estimator is found to produce a more precise estimate of the population size with a narrower 95% confidence interval as compared to several other contending estimators considered in this study.
ISSN:1552-387X
DOI:10.1177/00111287211014158