One-inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin


Inan G.

BIOMETRICAL JOURNAL, cilt.60, sa.4, ss.859-864, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Kısa Makale
  • Cilt numarası: 60 Sayı: 4
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1002/bimj.201700261
  • Dergi Adı: BIOMETRICAL JOURNAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.859-864
  • Anahtar Kelimeler: count data, mean parameterization, one-inflation, zero-truncation, MODEL
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this study, we would like to show that the one-inflated zero-truncated negative binomial (OIZTNB) regression model can be easily implemented in R via built-in functions when we use mean-parameterization feature of negative binomial distribution to build OIZTNB regression model. From the practitioners' point of view, we believe that this approach presents a computationally convenient way for implementation of the OIZTNB regression model.