Addressing overdispersion and zero-inflation for clustered count data via new multilevel heterogenous hurdle models
Yazarlar (1)
Doç. Dr. Yasin ALTINIŞIK Sinop Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Journal of Applied Statistics (Q2)
Dergi ISSN 0266-4763 Dergi Bilgileri (2023)
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2023
Kabul Tarihi 27-06-2022 Yayınlanma Tarihi 26-07-2022
Cilt / Sayı / Sayfa 50 / 2 / 408–433 DOI 10.1080/02664763.2022.2096875
Makale Linki https://figshare.com/articles/journal_contribution/Addressing_overdispersion_and_zero-inflation_for_clustered_count_data_via_new_multilevel_heterogenous_hurdle_models/20376790
UAK Araştırma Alanları
İstatistiksel Analiz Uygulamalı İstatistik Teorik İstatistik
Özet
Unobserved heterogeneity causing overdispersion and the excessive number of zeros take a prominent place in the methodological development on count modeling. An insight into the mechanisms that induce heterogeneity is required for better understanding of the phenomenon of overdispersion. When the heterogeneity is sourced by the stochastic component...
Anahtar Kelimeler
count data | Multilevel modeling | overdispersion | Poisson–Ailamujia distribution | Poisson–Lindley distribution | zero-inflation