%0 Journal Article
%T A Parametric Bayesian Approach in Density Ratio Estimation
%A Abdolnasser Sadeghkhani
%A Chunfang Devon Lin
%A Yingwei Peng
%J Stats | An Open Access Journal from MDPI
%D 2019
%R https://doi.org/10.3390/stats2020014
%X Abstract This paper is concerned with estimating the ratio of two distributions with different parameters and common supports. We consider a Bayesian approach based on the log¨CHuber loss function, which is resistant to outliers and useful for finding robust M-estimators. We propose two different types of Bayesian density ratio estimators and compare their performance in terms of frequentist risk function. Some applications, such as classification and divergence function estimation, are addressed. View Full-Tex
%K Bayes estimator
%K Bregman divergence
%K density ratio
%K exponential family
%K log¨CHuber loss
%U https://www.mdpi.com/2571-905X/2/2/14