Intrinsic priors for comparing zero-inflation parameters in Poisson models

Kipum Kim; Hyeon Jun Jeong; Seong Kim

Makale detayları

Intrinsic priors for comparing zero-inflation parameters in Poisson models

Yazarlar:

Kipum Kim | Hyeon Jun Jeong | Seong Kim

Yayıncı:

Hacettepe University

Ana Başlıklar:

Statistics

Dergi:

Hacettepe Journal of Mathematics and Statistics Vol.54 Issue 1, pp.319-335

Belge Tipi:

Makale

Yayın Tarihi:

2/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341747

pISSN:

2651-477X

Anahtar kelimeler:

Özet:

 Prior elicitation is an important issue in both objective and subjective Bayesian inferences. In hypothesis testing and model selection, choosing appropriate prior distributions becomes significantly more critical. In an objective Bayesian analysis, one utilizes noninformative priors such as Jeffreys priors or reference priors for hypothesis testing which are often improper, making unspecified constants to be contained in the Bayes factor. Thus, the resulting Bayes factor should be adjusted. In this paper, we consider default Bayes procedures for testing zero-inflation parameters in a zero-inflated Poisson distribution. In particular, we derive a set of intrinsic priors based on an approximation procedure. Extensive simulations and analyses of two real datasets are performed to support the methodology developed in the paper. It is shown that the proposed Bayesian and frequentist approaches yield similar comparable results.

 Prior elicitation is an important issue in both objective and subjective Bayesian inferences. In hypothesis testing and model selection, choosing appropriate prior distributions becomes significantly more critical. In an objective Bayesian analysis, one utilizes noninformative priors such as Jeffreys priors or reference priors for hypothesis testing which are often improper, making unspecified constants to be contained in the Bayes factor. Thus, the resulting Bayes factor should be adjusted. In this paper, we consider default Bayes procedures for testing zero-inflation parameters in a zero-inflated Poisson distribution. In particular, we derive a set of intrinsic priors based on an approximation procedure. Extensive simulations and analyses of two real datasets are performed to support the methodology developed in the paper. It is shown that the proposed Bayesian and frequentist approaches yield similar comparable results.

 Prior elicitation is an important issue in both objective and subjective Bayesian inferences. In hypothesis testing and model selection, choosing appropriate prior distributions becomes significantly more critical. In an objective Bayesian analysis, one utilizes noninformative priors such as Jeffreys priors or reference priors for hypothesis testing which are often improper, making unspecified constants to be contained in the Bayes factor. Thus, the resulting Bayes factor should be adjusted. In this paper, we consider default Bayes procedures for testing zero-inflation parameters in a zero-inflated Poisson distribution. In particular, we derive a set of intrinsic priors based on an approximation procedure. Extensive simulations and analyses of two real datasets are performed to support the methodology developed in the paper. It is shown that the proposed Bayesian and frequentist approaches yield similar comparable results.

 Prior elicitation is an important issue in both objective and subjective Bayesian inferences. In hypothesis testing and model selection, choosing appropriate prior distributions becomes significantly more critical. In an objective Bayesian analysis, one utilizes noninformative priors such as Jeffreys priors or reference priors for hypothesis testing which are often improper, making unspecified constants to be contained in the Bayes factor. Thus, the resulting Bayes factor should be adjusted. In this paper, we consider default Bayes procedures for testing zero-inflation parameters in a zero-inflated Poisson distribution. In particular, we derive a set of intrinsic priors based on an approximation procedure. Extensive simulations and analyses of two real datasets are performed to support the methodology developed in the paper. It is shown that the proposed Bayesian and frequentist approaches yield similar comparable results.

Makale detayları

Intrinsic priors for comparing zero-inflation parameters in Poisson models

Yazarlar:

Kipum Kim | Hyeon Jun Jeong | Seong Kim

Yayıncı:

Hacettepe University

Ana Başlıklar:

Statistics

Dergi:

Hacettepe Journal of Mathematics and Statistics Vol.54 Issue 1, pp.319-335

Belge Tipi:

Makale

Yayın Tarihi:

2/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341747

pISSN:

2651-477X

Fractional Bayes factor

intrinsic Bayes factor

intrinsic prior

training sample

Sayı

Makale detayları

Intrinsic priors for comparing zero-inflation parameters in Poisson models

Yazarlar: Kipum Kim | Hyeon Jun Jeong | Seong Kim

Yayıncı: Hacettepe University

Ana Başlıklar: Statistics

Dergi: Hacettepe Journal of Mathematics and Statistics Vol.54 Issue 1, pp.319-335

Belge Tipi: Makale

Yayın Tarihi: 2/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001341747

pISSN: 2651-477X

Fractional Bayes factor

intrinsic Bayes factor

intrinsic prior

training sample

Sayı

Yazarlar:

Kipum Kim | Hyeon Jun Jeong | Seong Kim

Yayıncı:

Hacettepe University

Ana Başlıklar:

Statistics

Dergi:

Hacettepe Journal of Mathematics and Statistics Vol.54 Issue 1, pp.319-335

Belge Tipi:

Makale

Yayın Tarihi:

2/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341747

pISSN:

2651-477X