Advances in Statistical Modeling: Copulas, Large Sample Theory and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 1660
Special Issue Editor
Interests: probability theory (stochastic processes, Markov and reversible Markov chains, central limit theorems, dependence coefficients and applications, copula models); statistics (kernel estimation of dependent data, Bayesian analysis, survival analysis, time series analysis, estimation methods, modeling and testing with Markov chains, large sample theory, regression analysis, ANOVA)
Special Issue Information
Dear Colleagues,
This volume is focused on recent advances in copula theory. It covers construction methods for copulas, modeling with copulas, Copula-based Markov chains, Mixing for Markov chains, measures of association, estimation problems and related large sample theories. Any applications of these topics will be considered. We are interested in models with sound theoretical novelty or that extend existing copula models to wider and more flexible families. We are particularly interested in applications involving survival analysis, time series, Bayesian analysis and regression, but any other areas are also welcome.
Dr. Martial Longla
Guest Editor
Manuscript Submission Information
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Keywords
- copula theory
- mixing structure
- large sample theory
- copula-based Markov chains
- new estimation methods
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