Sum of Bernoulli Mixtures: Beyond Conditional Independence
Joint Authors
Source
Journal of Probability and Statistics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-02
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Bae, Taehan& Iscoe, Ian. 2014. Sum of Bernoulli Mixtures: Beyond Conditional Independence. Journal of Probability and Statistics،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1042842
Modern Language Association (MLA)
Bae, Taehan& Iscoe, Ian. Sum of Bernoulli Mixtures: Beyond Conditional Independence. Journal of Probability and Statistics No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1042842
American Medical Association (AMA)
Bae, Taehan& Iscoe, Ian. Sum of Bernoulli Mixtures: Beyond Conditional Independence. Journal of Probability and Statistics. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1042842
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1042842