Conditions for interior based constrained prior distributions to ensure probability density
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 26
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شناسه ملی سند علمی:
JR_JSMTA-3-2_009
تاریخ نمایه سازی: 23 خرداد 1403
چکیده مقاله:
In Bayesian inference, the acquisition of prior distributions plays a fundamental role. While authorized priors need not conform to traditional probability densities and may be improper priors, obtaining proper prior densities remains a challenge in the Bayesian literature. This article explores a set of conditions that enable the establishment of specific assumptions, ensuring that maximum entropy priors and restricted reference priors become proper and transform into probability density priors. By examining these conditions, this study contributes to the advancement of proper prior acquisition in Bayesian analysis.
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نویسندگان
Amirhossein Ghatari
Department of Statistics, Amirkabir University of Technology, Tehran, Iran
Elham Tabrizi
Department of Mathematics, Kharazmi University, Tehran, Iran