Volume 10, Number 2 (November 2011)                   JIRSS 2011, 10(2): 95-107 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Fraser D A S, Naderi A, Ji K, Lin W, Su J. Exponential Models: Approximations for Probabilities. JIRSS. 2011; 10 (2) :95-107
URL: http://jirss.irstat.ir/article-1-158-en.html

Abstract:   (7467 Views)
Welch & Peers (1963) used a root-information prior to obtain posterior probabilities for a scalar parameter exponential model and showed that these Bayes probabilities had the confidence property to second order asymptotically. An important undercurrent of this indicates that the constant information reparameterization provides location model structure, for which the confidence property was and is well known. This paper examines the role of the scalar-parameter exponential model for obtaining approximate probabilities and approximate confidence levels, and then addresses the extension for the vector-parameter exponential model.
Full-Text [PDF 111 kb]   (1949 Downloads)    
Subject: 60: Probability theory and stochastic processes
Received: 2011/11/7 | Accepted: 2015/09/12

Add your comments about this article : Your username or email:
Write the security code in the box

© 2015 All Rights Reserved | Journal of The Iranian Statistical Society