Browsing by Author "Bayramoglu, K."

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Citation - WoS: 9
Citation - Scopus: 10
Baker-Lin Type Bivariate Distributions Based on Order Statistics
(Taylor & Francis Inc, 2014) Bayramoglu, K.; Bayramoglu (Bairamov), I.
Baker (2008) introduced a new class of bivariate distributions based on distributions of order statistics from two independent samples of size n. Lin and Huang (2010) discovered an important property of Baker's distribution and showed that the Pearson's correlation coefficient for this distribution converges to maximum attainable value, i.e., the correlation coefficient of the Frechet upper bound, as n increases to infinity. Bairamov and Bayramoglu (2013) investigated a new class of bivariate distributions constructed by using Baker's model and distributions of order statistics from dependent random variables, allowing higher correlation than that of Baker's distribution. In this article, a new class of Baker's type bivariate distributions with high correlation are constructed based on distributions of order statistics by using an arbitrary continuous copula instead of the product copula.
Citation - WoS: 17
Citation - Scopus: 19
From the Huang-Kotz Fgm Distribution To Baker's Bivariate Distribution
(Elsevier Inc, 2013) Bairamov, I; Bayramoglu, K.
Huang and Kotz (1999) [17] considered a modification of the Farlie-Gumbel-Morgenstern (FGM) distribution, introducing additional parameters, and paved the way for many research papers on modifications of FGM distributions allowing high correlation. The first part of the present paper is a review of recent developments on bivariate Huang-Kotz FGM distributions and their extensions. In the second part a class of new bivariate distributions based on Baker's system of bivariate distributions is considered. It is shown that for a model of a given order, this class of distributions with fixed marginals which are based on pairs of order statistics constructed from the bivariate sample observations of dependent random variables allows higher correlation than Baker's system. It also follows that under certain conditions determined by Lin and Huang (2010) [21], the correlation for these systems converges to the maximum Frechet-Hoeffding upper bound as the sample size tends to infinity. (C) 2011 Elsevier Inc. All rights reserved.