Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Longla, Martial"'
Autor:
Muia, Mathias N., Longla, Martial
This paper examines the impact of discrete marginal distributions on copula-based Markov chains. We present results on mixing and parameter estimation for a copula-based Markov chain model with Bernoulli($p$) marginal distribution and highlight the d
Externí odkaz:
http://arxiv.org/abs/2407.12308
Autor:
Longla, Martial, Hamadou, Mous-Abou
This work provides a study of parameter estimators based on functions of Markov chains generated by some perturbations of the independence copula. We provide asymptotic distributions of maximum likelihood estimators and confidence intervals for copul
Externí odkaz:
http://arxiv.org/abs/2308.14282
Autor:
Longla, Martial
We characterize absolutely continuous symmetric copulas with square integrable densities in this paper. This characterization is used to create new copula families, that are perturbations of the independence copula. The full study of mixing propertie
Externí odkaz:
http://arxiv.org/abs/2308.11074
This paper brings some insights of $\psi'$-mixing, $\psi^*$-mixing and $\psi$-mixing for copula-based Markov chains and the perturbations of their copulas. We provide new tools to check Markov chains for $\psi$-mixing or $\psi'$-mixing, and also show
Externí odkaz:
http://arxiv.org/abs/2111.14682
This paper explores the impact of perturbations of copulas on dependence properties of the Markov chains they generate. We use an observation that is valid for convex combinations of copulas to establish sufficient conditions for the mixing coefficie
Externí odkaz:
http://arxiv.org/abs/2106.05766
This paper explores the impact of perturbations of copulas on the dependence properties of the Markov chains they generate. We consider Markov chains generated by perturbed copulas. Results are provided for the mixing coefficients $\beta_n$, $\psi_n$
Externí odkaz:
http://arxiv.org/abs/2101.04573
Autor:
Longla, Martial1 (AUTHOR) mlongla@olemiss.edu
Publikováno v:
Statistical Papers. Sep2024, Vol. 65 Issue 7, p4331-4363. 33p.
Autor:
Longla, Martial, Sivaganesan, Siva
We provide a probabilistic approach to modeling the movements of subjects through multiple stages, with "stays" or survival at each stage for a random length of time, and ending at a desired final stage. We use conditional Markov chains with exponent
Externí odkaz:
http://arxiv.org/abs/1801.04490
Autor:
Longla, Martial, Peligrad, Magda
The goal of this paper is to indicate a new method for constructing normal confidence intervals for the mean, when the data is coming from stochastic structures with possibly long memory, especially when the dependence structure is not known or even
Externí odkaz:
http://arxiv.org/abs/1801.00175
Autor:
Longla, Martial
This dissertation is concerned with the notion of copula and its importance in modeling and estimation. We use the theory of copulas to assess dependence properties of stationary Markov chains and convergence to the Brownian motion. In the introducto
Externí odkaz:
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1367944672