AŞIRI SIFIR DURUMUNDA BAZI SAYIM MODELLERİNİN KARŞILAŞTIRILMASI: BİR UYGULAMA

Öz

Sayma verileri için literatürde farklı regresyon modelleri geliştirilmiştir. Bunlar arasında en bilinen regresyon modelleri Poisson ve negatif binomial regresyon modelleridir. Poisson ya da negatif binomial modeller eğer fazla sıfır değerli terimler yoksa uygun olur. Sayma verilerinde aşırı sıfır olduğunda eşit yayılım durumunda zero-inflated Poisson, aşırı yayılım durumunda zero-inflated negatif binom modelleri en çok tercih edilen modellerdir. Çok fazla sıfır olması durumunda kullanılan başka bir model de Poisson Hurdle ve negatif binomial Hurdle modelleridir. Bu çalışmada örnek bir veri seti için bu modeller karşılaştırılmıştır. Bu amaçla LL, AIC, BIC ve Vuong test istatistiği kullanılmıştır.

Anahtar Kelimeler

• Hurdle model
• negatif binomial model
• poisson model
• sayma verisi
• sıfır şişirilmiş modeller

COMPARISON OF SOME COUNT MODELS IN CASE OF EXCESSIVE ZEROS: AN APPLICATION

Öz

Different regression models have been developed in the literature for count data. Among these, the most well-known regression models are Poisson and negative binomial regression models. Poisson or negative binomial models are suitable if there are not many zero-valued terms. When there are excessive zeros in count data, zero-inflated Poisson models are the most preferred models in the case of equal dispersion, and zero-inflated negative binomial models are the most preferred models in case of overdispersion. Other models used in the case of too many zeros are the Poisson Hurdle and negative binomial Hurdle models. In this study, these models are compared for a sample data set. For this purpose, LL, AIC, BIC and Vuong test statistics were used.

Anahtar Kelimeler

• Count data
• Hurdle model
• negative binomial model
• poisson model
• zero-ınflated models.

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