Generalized Marshall-Olkin Distributions, and Related Bivariate Aging Properties

National Natural Science Foundation of China [10771090]A class of generalized bivariate Marshall-Olkin distributions, which includes as special cases the Marshall-Olkin bivariate exponential distribution and the Marshall-Olkin type distribution due to Muliere and Scarsini (1987) [19] are examined in this paper. Stochastic comparison results are derived, and bivariate aging properties, together with properties related to evolution of dependence along time, are investigated for this class of distributions. Extensions of results previously presented in the literature are provided as well. (C) 2011 Elsevier Inc. All rights reserved

Generalized Exponential Models with Applications

We introduce a generalized exponential model whose exact moments and normalizing constant are obtained in terms of Meijer’s generalized hypergeometric G-function. Actually, several widely utilized statistical distributions such as the gamma, Weibull and half-normal constitute particular cases thereof. The generalized inverse Gaussian distribution, which was popularized in the late seventies by Ole Barndor_Neilsen, is also extended by incorporating an additional parameter in its density function, the moments of the resulting distribution being expressed in terms of Bessel functions. A number of data sets were then fitted with diverse exponential-type models for comparison purposes. Additionally, it is shown that the inverse Mellin transform technique may be employed to derive a multiple series representation of the density function of linear combinations of chi-square random variables, which are encountered for instance in connection with the distribution of certain quadratic forms and some asymptotic distributional results arising in multivariate analysis. The accuracy of the truncated form of this density function is compared to that obtained from a reparameterized generalized gamma distribution. A methodology whereby regression problems are converted into density estimation problems is also proposed and applied to certain actuarial data sets. A technique for modeling bivariate observations is presented as well

Estimators for the parameter mean of Morgenstern type bivariate generalized exponential distribution using ranked set sampling

In situations where the sampling units in a study can be more easily ranked based on the measurement of an auxiliary variable, ranked set sampling provides unbiased estimators for the mean of a population that are more efficient than unbiased estimators based on simple random sampling. In this paper, we consider the Morgenstern type bivariate generalized exponential distribution and obtain several unbiased estimators for the mean parameter of its marginal distribution, based on different ranked set sampling schemes. The efficiency of all considered estimators are evaluated and several numerical illustrations are given

Estimators for the parameter mean of Morgenstern type bivariate generalized exponential distribution using ranked set sampling

In situations where the sampling units in a study can be more easily ranked based on the measurement of an auxiliary variable, ranked set sampling provides unbiased estimators for the mean of a population that are more efficient than unbiased estimators based on simple random sampling. In this paper, we consider the Morgenstern type bivariate generalized exponential distribution and obtain several unbiased estimators for the mean parameter of its marginal distribution, based on different ranked set sampling schemes. The efficiency of all considered estimators are evaluated and several numerical illustrations are given.Peer Reviewe