This paper introduces a new generalization of the Pareto distribution using the MarshallOlkin generator and the method of alpha power transformation. This new model has several desirable properties appropriate for modelling right skewed data. The Authors demonstrate how the hazard rate function...

We investigate the problem of simultaneous estimation of multivariate normal mean vector using Zellner (1994)’s balance loss function when common variance σ2 is unknown. We first find a class of minimax estimators for this problem which extends a class given by Chung et al. (1999). This...

In this paper, maximum likelihood and Bayesian approaches have been used to obtain the estimation of <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$P(XY)$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mi>P</mi> <mo stretchy="false">(</mo> <mi>X</mi> <mo></mo> <mi>Y</mi> <mo stretchy="false">)</mo> </mrow> </math> </EquationSource> </InlineEquation> based on a set of upper record values from Kumaraswamy distribution. The existence and uniqueness of the maximum likelihood estimates of the Kumaraswamy distribution...</equationsource></equationsource></inlineequation>

New inferential procedures for the geometric distribution, based on δ-records, are developed. Maximum likelihood and Bayesian approaches for parameter estimation and prediction of future records are considered. The performance of the estimators is compared with those based solely on...

Under normality, the Bayesian estimation problem, the best linear unbiased estimation problem, and the restricted least-squares problem are all equivalent. As a result we need not compute pseudo-inverses and other complicated functions, which will be impossible for large sparse systems. Instead,...