The uniform CLT for the empirical estimator of countable state space semi-Markov kernels indexed by functions with applications
DOI10.1080/10485252.2022.2071889OpenAlexW4229458193MaRDI QIDQ5051325
Salim Bouzebda, Nikolaos Limnios
Publication date: 23 November 2022
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485252.2022.2071889
functional central limit theoreminvariance principlesemi-Markov processempirical estimatorsemi-Markov kernel
Bootstrap, jackknife and other resampling methods (62F40) Markov renewal processes, semi-Markov processes (60K15) Exchangeability for stochastic processes (60G09) Applications of continuous-time Markov processes on discrete state spaces (60J28) Nonparametric inference (62Gxx)
Cites Work
- Exchangeably weighted bootstraps of empirical estimators of a semi-Markov kernel
- Asymptotic behavior of weighted multivariate Cramér-von Mises-type statistics under contiguous alternatives
- On general bootstrap of empirical estimator of a semi-Markov kernel with applications
- Empirical and sequential empirical copula processes under serial dependence
- Some new multivariate tests of independence
- Conditional copulas, association measures and their applications
- Semi-Markov chains and hidden semi-Markov models toward applications. Their use in reliability and DNA analysis.
- Semi-Markov reliability models with recurrence times and credit rating applications
- Approximation theorems for independent and weakly dependent random vectors
- Some central limit theorems for \(\ell^\infty\)-valued semimartingales and their applications
- General tests of independence based on empirical processes indexed by functions
- Weak convergence and empirical processes. With applications to statistics
- On the strong approximation of bootstrapped empirical copula processes with applications
- Strong approximation of multidimensional \(\mathbb P\)-\(\mathbb P\) plots processes by Gaussian processes with applications to statistical tests
- Introduction to empirical processes and semiparametric inference
- A multidimensional functional central limit theorem for an empirical estimator of a continuous-time semi-Markov kernel
- Regenerative stochastic processes
- Remarks on Some Nonparametric Estimates of a Density Function
- THE UNIFORM CLT FOR MARTINGALE DIFFERENCE ARRAYS UNDER THE UNIFORMLY INTEGRABLE ENTROPY
- Uniform Central Limit Theorems
- On a multidimensional general bootstrap for empirical estimator of continuous-time semi-Markov kernels with applications
- The uniform CLT for empirical estimator of a general state space semi-Markov kernel indexed by functions
- A functional central limit theorem for the empirical estimator of a semi-Markov kernel
- Central limit theorems for multivariate semi-Markov sequences and processes, with applications
- THE SECOND CENTRAL LIMIT THEOREM FOR MARTINGALE DIFFERENCE ARRAYS
- Continuous Semi‐Markov Processes
- Some New Estimates for Distribution Functions
- Markov Renewal Processes with Finitely Many States
- Weak convergence of probability measures and random functions in the function space D[0,∞)
- Markov Renewal Processes: Definitions and Preliminary Properties
- On Estimation of a Probability Density Function and Mode
- Minimum divergence estimators for the Radon–Nikodym derivatives of the semi-Markov kernel
- Convergence of stochastic processes
- Statistical models based on counting processes
- Semi-Markov processes and reliability
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: The uniform CLT for the empirical estimator of countable state space semi-Markov kernels indexed by functions with applications