Bivariate Marshall Olkin distribution methods are very useful for modelling failure of paired organs, such as the eyes, kidneys, and lungs. Although there are inevitable relations between the components of such organs, these organs may possibly fail one after the other or at the same time. In this paper, a new model using Bivariate Marshall- Olkin distribution methods, namely Bivariate Omega Model (BOM) is introduced and applied for modeling time of two eyes blindness in diabetic retinopathy patients. Some probabilistic properties of the bivariate Omega distribution are derived and studied. The dependence properties for bivariate Omega distribution are proposed using the Marshall-Olkin copula. Parameters estimators are investigated using the maximum likelihood method. Two data sets are illustrated to show the usefulness of the new model for fitting such data.
M. Kilany, N. and M. Seyam, M.
"Marshall–Olkin Bivariate Omega Model for Modeling Failure of Paired Organs,"
Information Sciences Letters: Vol. 12
, PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol12/iss11/27