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Activity Number: 245 - Bayesian Models for Clustering and Latent Allocation
Type: Contributed
Date/Time: Tuesday, August 9, 2022 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract #323638
Title: Bayesian Regression Modeling of 0-1 Data Having Boundary Values
Author(s): Eugene D Hahn*
Companies: Salisbury University
Keywords: Proportion data; Finite mixture modeling; Bayesian inference; Markov chain Monte Carlo

Regression modeling of percentages or normalized rates occurs in a variety of fields. Most long-standing techniques, however, are hampered by the presence of boundary values of zero or one. Boundary-inflated likelihood functions are one way of addressing this issue. However these approaches treat boundary values as arising independently from non-boundary values. We instead examine continuous regression modeling of proportions with boundary values using functionals of beta and triangular distributions.

Authors who are presenting talks have a * after their name.

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