New zero-inflated regression models with a variant of censoring
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Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Brazilian Statistical Association
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
There is ever growing demand of modeling overdispersed count data generated by various disiplines. Excessive number of zeros and hetero-geneity in the population are two main sources of the overdispersion problem. Development of new count models that are more flexible than conventional Poisson model is thus necessary in order to address such sources. This study fullfils this need by proposing a new heterogeneous Poisson model with a cap-ture of excess zeros, namely zero-inflated Poisson-Ailamujia (ZIPA) model. In line with the aim of curing overdispersion, a censored variant of this newly suggested model is also here developed. An extensive simulation study is conducted to assess the performances of both forms of new models in terms of bias, precision and accuracy measures. Additionally, two real world ap-plications are presented to illustrate practical implications of zero-inflated (censored) Poisson-Ailamujia models in comparison to some alternatives.
Açıklama
Anahtar Kelimeler
Lifetime datasets, zero-inflation, count regression, compound Poisson, overdispersion, censoring, Poisson-Ailamujia model
Kaynak
Brazilian Journal of Probability and Statistics
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
36
Sayı
4
