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Bayesian inference for P (X<Y) using asymmetric dependent distributions
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Rubio, Francisco J. and Steel, Mark F. J. (2013) Bayesian inference for P (X<Y) using asymmetric dependent distributions. Bayesian Analysis, Volume 8 (Number 1). pp. 43-62. doi:10.1214/13-BA802 ISSN 1931-6690.
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Official URL: http://dx.doi.org/10.1214/13-BA802
Abstract
This paper studies Bayesian inference for θ=P(X<Y) in the case where the marginal distributions of X and Y belong to classes of distributions obtained by skewing scale mixtures of normals. We separately address the cases where X and Y are independent or dependent random variables. Dependencies between X and Y are modelled using a Gaussian copula. Noninformative benchmark and vague priors are provided for these scenarios and conditions for the existence of the posterior distribution of θ are presented. We show that the use of the Bayesian models proposed here is also valid in the presence of set observations. Examples using simulated and real data sets are presented.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Bayesian Analysis | ||||
Publisher: | International Society for Bayesian Analysis | ||||
ISSN: | 1931-6690 | ||||
Official Date: | March 2013 | ||||
Dates: |
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Volume: | Volume 8 | ||||
Number: | Number 1 | ||||
Page Range: | pp. 43-62 | ||||
DOI: | 10.1214/13-BA802 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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