Prior Distribution Classes with Comprehensive Coverage

Abstract

The Bayes’ theorem which is the kernel of today’s Bayesian World incorporates prior knowledge in analysis. Regarding its level, form or application restrictions, the challenging part can be seen as “prior” especially for joiners in this world. In various areas, concerning the requirements, there are various prior distributions suggested to be used. However the studies that give a generic look and review on prior distributions classes are not seen in the literature. With this motivation, the paper discusses prior distributions with comprehensive coverage. Thus it’s aimed to introduce prior distribution classes and to give a review on them.

Keywords

• Classes of prior distributions
• Informative priors
• Non-informative priors

Kapsamlı Bir İçerikle Ön Dağılım Türleri

Abstract

Bayesyen analizlerin özünü oluşturan Bayes Teoremi, analizlere ön bilgiyi dahil ederek istatistiksel süreci gerçekleştirmektedir. Ön bilginin düzeyi, yapısı ve uygulama sınırları gözönüne alınınca, özellikle bu alanda yeni çalışan araştırmacılar için en zorlayıcı kısmı “ön dağılım” olarak görülebilir. Farklı alanlarda ihtiyaç doğrultusunda önerilen çeşitli ön dağılım türleri vardır. Öte yandan ön dağılımlar üzerine jenerik bir bakışı yansıtan ve gözden geçirme niteliğinde çalışma literatürde mevcut değildir. Bu motivasyonla, çalışma ön dağılım türlerini kapsamlı bir içerikle ele almaktadır. Böylelikle araştırmacılara ön dağılım türlerinin tanıtımı ve bunlarla ilgili genel bir bakış kazandırmak amaçlanmaktadır.

Keywords

• Ön dağılım türleri
• Bilgi veren ön dağılımlar
• Bilgi vermeyen ön dağılımlar

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