Sum of Bernoulli Mixtures: Beyond Conditional Independence. (2nd June 2014)

• Record Type: Journal Article
• Authors: Bae, Taehan; Iscoe, Ian
• Other Names: Thavaneswaran Aera Academic Editor.
• Is Part Of: Journal of probability and statistics. Volume 2014(2014)
• Publication Date: 2014-06-02
• Subjects: Probabilities -- Periodicals; Mathematical statistics -- Periodicals; Mathematical statistics; Probabilities; Periodicals; 519
• DOI: 10.1155/2014/838625
• Languages: English
• ISSNs: 1687-952X

Abstract

Abstract : We consider the distribution of the sum of Bernoulli mixtures under a general dependence structure. The level of dependence is measured in terms of a limiting conditional correlation between two of the Bernoulli random variables. The conditioning event is that the mixing random variable is larger than a threshold and the limit is with respect to the threshold tending to one. The large-sample distribution of the empirical frequency and its use in approximating the risk measures, value at risk and conditional tail expectation, are presented for a new class of models which we call double mixtures . Several illustrative examples with a Beta mixing distribution, are given. As well, some data from the area of credit risk are fit with the models, and comparisons are made between the new models and also the classical Beta-binomial model.