3941

Omid M. Ardakani, Majid Asadi, Nader Ebrahimi, and Ehsan S. Soofi

خبرنامه انجمن آمار ايران (JIRSS)

تهران :انجمن آمار ايران

2021

20

1

27-59

Arithmetic Mixture , Geometric Mixture , Jensen-Shannon , Kullback-Leibler

In recent years, we have studied information properties of various types of mixtures of probability distributions and introduced a new type, which includes previously known mixtures as special cases. These studies are disseminated in dierent fields: reliability engineering, econometrics, operations research, probability, the information theory, and data mining. This paper presents a holistic view of these studies and provides further insights and examples. We note that the insightful probabilistic formulation of the mixing parameters stipulated by Behboodian (1972) is required for a representation of the well-known information measure of the arithmetic mixture. Applications of this information measure presented in this paper include lifetime modeling, system reliability, measuring uncertainty and disagreement of forecasters, probability modeling with partial information, and information loss of kernel estimation. Probabilistic formulations of the mixing weights for various types of mixtures provide the Bayes-Fisher information and the Bayes risk of the mean residual function.