:: Volume 8, Issue 1 (9-2011) ::
JSRI 2011, 8(1): 29-48 Back to browse issues page
A Note on the Bivariate Maximum Entropy Modeling
S. Ashrafi, M. Asadi *1
1- , m.asadi@sci.ui.ac.ir
Abstract:   (3145 Views)

Let X=(X1 ,X2 ) be a continuous random vector. Under the assumption that the marginal distributions of Xand X2 are given, we develop models for vector X when there is partial information about the dependence structure between X and X2. The models which are obtained based on well-known Principle of Maximum Entropy are called the maximum entropy (ME) models. Our results lead to characterization of some well-known bivariate distributions such as Generalized Gumbel, Farlie-Gumbel-Morgenstern and Clayton bivariate distributions. The relationship between ME models and some well known dependence notions are studied. Conditions under which the mixture of bivariate distributions are ME models are also investigated.

Keywords: . Fréchet class of distributions, hazard gradient, dependence, total positive of order 2.
Full-Text [PDF 216 kb]   (1431 Downloads)    
Type of Study: Research | Subject: General
Received: 2015/12/30 | Accepted: 2015/12/30 | Published: 2015/12/30



XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 8, Issue 1 (9-2011) Back to browse issues page