Construction of bivariate and multivariate weighted distributions via conditioning |
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Authors: | Barry C Arnold Indranil Ghosh Ayman Alzaatreh |
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Institution: | 1. Department of Statistics, University of California, Riverside, CA, USA;2. Department of Mathematics and Statistics, University of North Carolina, Wilmington, NC, USA;3. Department of Mathematics, Nazarbayev University, Astana, Kazakhstan |
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Abstract: | Weighted distributions (univariate and bivariate) have received widespread attention over the last two decades because of their flexibility for analyzing skewed data. In this article, we propose an alternative method to construct a new family of bivariate and multivariate weighted distributions. For illustrative purposes, some examples of the proposed method are presented. Several structural properties of the bivariate weighted distributions including marginal distributions together with distributions of the minimum and maximum, evaluation of the reliability parameter, and verification of total positivity of order two are also presented. In addition, we provide some multivariate extensions of the proposed models. A real-life data set is used to show the applicability of these bivariate weighted distributions. |
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Keywords: | Bivariate weighted Pareto II distribution increasing and decreasing failure rate Laplace transform multivariate weighted Pareto II distribution total positivity of order two weighted distributions |
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