Results 1 to 10 of about 299 (140)
Frontiers in Applied Mathematics and Statistics, 2023 The composite length-biased exponential-Pareto (CLBEP) distribution is a new composite distribution that is introduced in this article. This model's probability density function, moments, and quantiles, among other statistical characteristics, are ...
Moulouk Halima Benchettah +2 more
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A superior extension for the Lomax distribution with application to Covid-19 infections real data [PDF]
Alexandria Engineering Journal, 2022 We present a new continuous lifetime model with four parameters by combining the Lomax and the Weibull distributions. The extended odd Weibull Lomax (EOWL) distribution is what we’ll call it.
Hassan Alsuhabi +7 more
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A new extended rayleigh distribution with applications of COVID-19 data [PDF]
Results in Physics, 2021 This paper aims to model the COVID-19 mortality rates in Italy, Mexico, and the Netherlands, by specifying an optimal statistical model to analyze the mortality rate of COVID-19.
Hisham M. Almongy +4 more
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Insights on the trend of the Novel Coronavirus 2019 series in some Small Island Developing States: A Thinning-based Modelling Approach [PDF]
Alexandria Engineering Journal, 2021 Undeniably, the Novel Coronavirus 2019, (COVID-19), has disrupted the routine functioning of the global economic and social activities. In particular, vulnerable economies such as the Small Island Developing states (SIDs) are facing unprecedented health ...
Naushad Mamode Khan +3 more
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On copulas of self-similar Ito processes
Dependence Modeling, 2021 We characterize the cumulative distribution functions and copulas of two-dimensional self-similar Ito processes, with randomly correlated Wiener margins, as solutions of certain elliptic partial differential equations.
Jaworski Piotr, Krzywda Marcin
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Sklar’s theorem, copula products, and ordering results in factor models
Dependence Modeling, 2021 We consider a completely specified factor model for a risk vector X = (X1, . . ., Xd), where the joint distributions of the components of X with a risk factor Z and the conditional distributions of X given Z are specified.
Ansari Jonathan, Rüschendorf Ludger
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Functions operating on several multivariate distribution functions
Dependence Modeling, 2023 Functions ff on [0,1]m{\left[0,1]}^{m} such that every composition f∘(g1,…,gm)f\circ \left({g}_{1},\ldots ,{g}_{m}) with dd-dimensional distribution functions g1,…,gm{g}_{1},\ldots ,{g}_{m} is again a distribution function, turn out to be characterized ...
Ressel Paul
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Stable tail dependence functions – some basic properties
Dependence Modeling, 2022 We prove some important properties of the extremal coefficients of a stable tail dependence function (“STDF”) and characterise logistic and some related STDFs.
Ressel Paul
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Dependence uncertainty bounds for the energy score and the multivariate Gini mean difference
Dependence Modeling, 2020 The energy distance and energy scores became important tools in multivariate statistics and multivariate probabilistic forecasting in recent years. They are both based on the expected distance of two independent samples. In this paper we study dependence
Bernard Carole, Müller Alfred
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Maximal asymmetry of bivariate copulas and consequences to measures of dependence
Dependence Modeling, 2022 In this article, we focus on copulas underlying maximal non-exchangeable pairs (X,Y)\left(X,Y) of continuous random variables X,YX,Y either in the sense of the uniform metric d∞{d}_{\infty } or the conditioning-based metrics Dp{D}_{p}, and analyze their ...
Griessenberger Florian +1 more
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