Constructing and generalizing multivariate copulas: a generalizing approach [PDF]
Recently, Liebscher (2006) introduced a general construction scheme of d-variate copulas which generalizes the Archimedean family. Similarly, Morillas (2005) proposed a method to obtain a variety of new copulas from a given d-copula.
Fischer, Matthias J., Köck, Christian
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A new bivariate Poisson distribution via conditional specification: properties and applications. [PDF]
J Appl Stat, 2021 Ghosh I, Marques F, Chakraborty S.
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Some results on weak and strong tail dependence coefficients for means of copulas [PDF]
Copulas represent the dependence structure of multivariate distributions in a natural way. In order to generate new copulas from given ones, several proposals found its way into statistical literature.
Fischer, Matthias J., Klein, Ingo
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Interactive Visualization and Computation of 2D and 3D Probability Distributions. [PDF]
SN Comput Sci, 2022 Bobrovnikov M, Chai JT, Dinov ID.
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Considering the temporal interdependence of human mobility and COVID-19 concerning Indonesia's large-scale social distancing policies. [PDF]
Qual Quant, 2023 Ahdika A, Primandari AH, Adlin FN.
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Copula-based models for multivariate discrete response data [PDF]
, 2013 Nikoloulopoulos, Aristidis K
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Copula-based measures of asymmetry between the lower and upper tail probabilities. [PDF]
Stat Pap (Berl), 2022 Kato S, Yoshiba T, Eguchi S.
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A New Family of Continuous Probability Distributions. [PDF]
Entropy (Basel), 2021 El-Morshedy M +4 more
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Investigating meteorological/groundwater droughts by copula to study anthropogenic impacts. [PDF]
Sci Rep, 2022 Sadeghfam S +4 more
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Uni-variate and bi-variate Inverted Exponential Teissier distribution in Bayesian and non-Bayesian framework to model stochastic dynamic variation of climate data. [PDF]
Theor Appl Climatol, 2022 Thakur D, Bhattacharya S, Das I.
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