Electronic Theses and Dissertations

Date of Award

1-1-2025

Document Type

Dissertation

Degree Name

Ph.D. in Mathematics

First Advisor

Martial Longla

Second Advisor

Xin Dang

Third Advisor

Hailin Sang

School

University of Mississippi

Relational Format

dissertation/thesis

Abstract

This dissertation explores continuous-state stationary reversible Markov chains generated by a new family of absolutely continuous symmetric copulas that have square-integrable densities. We examine and define parameter estimation techniques for the Markov chains generated by the new family of copulas and different marginals. Furthermore, we provide the joint limiting distributions and confidence intervals/regions of these estimators. We also look into the parameter estimation and it’s limiting distributions for bivariate independent data generated by the new family of copula and various marginal distributions. A simulation study using R is proposed to support our findings.

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