TY - JOUR
T1 - Variants of Mixtures
T2 - Information Properties and Applications
AU - Ardakani, Omid
AU - Asadi, Majid
AU - Ebrahimi, Nader
AU - Soofi, Ehsan
N1 - Publisher Copyright:
© 2021,Journal of the Iranian Statistical Society. All rights reserved.
PY - 2021
Y1 - 2021
N2 - 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 different 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.
AB - 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 different 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.
KW - Arithmetic Mixture
KW - Geometric Mixture
KW - Jensen-Shannon
KW - Kullback-Leibler
UR - http://www.scopus.com/inward/record.url?scp=85115638141&partnerID=8YFLogxK
U2 - 10.52547/jirss.20.1.27
DO - 10.52547/jirss.20.1.27
M3 - Article
SN - 1726-4057
VL - 20
SP - 27
EP - 59
JO - Journal of the Iranian Statistical Society
JF - Journal of the Iranian Statistical Society
IS - 1
ER -