The uniform CLT for the empirical estimator of countable state space semi-Markov kernels indexed by functions with applications

Salim Bouzebda and Nikolaos Limnios

Journal of Nonparametric Statistics, 2022, vol. 34, issue 4, 758-788

Abstract: This paper is concerned with the uniform CLT for an empirical estimator of countable state space semi-Markov processes indexed by functions under the uniformly integrable entropy condition. The results of this paper generalise those of Limnios [(2004), ‘A Functional Central Limit Theorem for the Empirical Estimator of a Semi-Markov Kernel’, Journal of Nonparametric Statistics, 16(1–2), 13–18. The International Conference on Recent Trends and Directions in Nonparametric Statistics]. We apply our results to the following important topics: on the kernel-type estimator of the semi-Markov kernel, the weak convergence of the smoothed empirical semi-Markov processes, we introduce the copula estimators in the semi-Markov framework and we establish their limiting laws by using the functional delta methods. We prove the main results for the uniform CLT via a martingale difference sequence as in Bae et al. [(2010), ‘The Uniform CLT for Martingale Difference Arrays Under the Uniformly Integrable Entropy’, Bulletin of the Korean Mathematical Society, 47(1), 39–51].

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/10485252.2022.2071889 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gnstxx:v:34:y:2022:i:4:p:758-788

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

DOI: 10.1080/10485252.2022.2071889

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

More articles in Journal of Nonparametric Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().