Continuous displacement interpolation between checkerboard copulas
Dependence ModelingThis paper presents a displacement-like interpolation method between any two given checkerboard copulas. This interpolation is close to the geodesic connecting the two checkerboard copulas in the L 2-Wasserstein space, which, however, leaves the copula ...
Grothe Oliver, Luo Na
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Dependence modeling in general insurance using local Gaussian correlations and hidden Markov models
Dependence ModelingThis article introduces a hybrid framework that combines local Gaussian correlation (LGC) with hidden Markov models (HMMs) to model dynamic and nonlinear dependencies in general insurance claims, thereby addressing the limitations of static copula ...
Afazali Zabibu +4 more
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On comprehensive families of copulas involving the three basic copulas and transformations thereof
Dependence ModelingComprehensive families of copulas including the three basic copulas (at least as limit cases) are useful tools to model countermonotonicity, independence, and comonotonicity of pairs of random variables on the same probability space. In this contribution,
Saminger-Platz Susanne +4 more
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Protocol for executing and benchmarking eight computational doublet-detection methods in single-cell RNA sequencing data analysis. [PDF]
STAR Protoc, 2021 Xi NM, Li JJ.
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A dimension reduction for extreme types of directed dependence
Dependence ModelingIn recent years, a variety of novel measures of dependence have been introduced being capable of characterizing diverse types of directed dependence, hence diverse types of how a number of predictor variables X = (X 1, …, X p), p∈N $p\in \mathbb{N ...
Fuchs Sebastian, Limbach Carsten
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Estimating the parameters of a dependent model and applying it to environmental data set. [PDF]
J Appl Stat, 2023 Mohtashami-Borzadaran V +2 more
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On the rank-deficient canonical correlation technique solved by analytic spectral decomposition. [PDF]
J Appl Stat, 2022 Malec L.
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An Expectation-Maximization Algorithm for Combining a Sample of Partially Overlapping Covariance Matrices. [PDF]
Axioms, 2023 Akdemir D, Somo M, Isidro-Sanchéz J.
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The Kendall interaction filter for variable interaction screening in high dimensional classification problems. [PDF]
J Appl Stat, 2023 Anzarmou Y, Mkhadri A, Oualkacha K.
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Dependence ModelingBivariate time-to-event data often arise in various fields, including medicine, engineering, and economics, where understanding the association between two survival times is crucial. Traditional global association measures like Spearman’s rho and Kendall’
Sercik Ömer +2 more
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