Results 11 to 20 of about 69 (68)
Checkerboard copula defined by sums of random variables
Dependence Modeling, 2020 We consider the problem of finding checkerboard copulas for modeling multivariate distributions. A checkerboard copula is a distribution with a corresponding density defined almost everywhere by a step function on an m-uniform subdivision of the unit ...
Kuzmenko Viktor +2 more
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Some remarks on a pair of seemingly unrelated regression models
Open Mathematics, 2019 Linear regression models are foundation of current statistical theory and have been a prominent object of study in statistical data analysis and inference.
Hou Jian, Zhao Yong
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New copulas based on general partitions-of-unity (part III) — the continuous case
Dependence Modeling, 2019 In this paper we discuss a natural extension of infinite discrete partition-of-unity copulas which were recently introduced in the literature to continuous partition of copulas with possible applications in risk management and other fields.
Pfeifer Dietmar +3 more
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Statistical inference and data analysis of the record-based transmuted Burr X model
Open MathematicsProbability distribution has proven its usefulness in almost every discipline of human endeavors. A novel extension of Bur X distribution is developed in this study employing the record-based transmuted mapping technique, which can be used to fit skewed ...
Alrweili Hleil
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Dependence Modeling, 2013 We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
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A matrix approach to determine optimal predictors in a constrained linear mixed model
Open MathematicsFor a general vector of all unknown vectors in a constrained linear mixed model (CLMM), this study compared the dispersion matrices of the best linear unbiased predictors with any symmetric matrix for determining the optimality of predictors among others.
Güler Nesrin, Büyükkaya Melek Eriş
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Inference for copula modeling of discrete data: a cautionary tale and some facts
Dependence Modeling, 2017 In this note, we elucidate some of the mathematical, statistical and epistemological issues involved in using copulas to model discrete data. We contrast the possible use of (nonparametric) copula methods versus the problematic use of parametric copula ...
Faugeras Olivier P.
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Dependence measure for length-biased survival data using copulas
Dependence Modeling, 2019 The linear correlation coefficient of Bravais-Pearson is considered a powerful indicator when the dependency relationship is linear and the error variate is normally distributed.
Bentoumi Rachid +2 more
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Demonstratio MathematicaThe aim of this article is to study a semi-functional partial linear regression model (SFPLR) for spatial data with responses missing at random (MAR).
Benchikh Tawfik +3 more
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Volatility filtering in estimation of kurtosis (and variance)
Dependence Modeling, 2019 The kurtosis of the distribution of financial returns characterized by high volatility persistence and thick tails is notoriously difficult to estimate precisely.
Anatolyev Stanislav
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