On the asymptotic properties of some kernel estimators for continuous-time semi-Markov processes
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Publication:5078823
DOI10.1080/10485252.2022.2044033OpenAlexW4214834612MaRDI QIDQ5078823
Fatiha Mokhtari, Saâdia Rahmani, Chafiâa Ayhar, Vlad Stefan Barbu
Publication date: 25 May 2022
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485252.2022.2044033
Inference from stochastic processes (62Mxx) Stochastic processes (60Gxx) Nonparametric inference (62Gxx) Limit theorems in probability theory (60Fxx)
Cites Work
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- Exact MLE and asymptotic properties for nonparametric semi-Markov models
- Asymptotic normality of the kernel estimate under dependence conditions: Application to hazard rate
- Strong consistency of kernel density estimates for Markov chains failure rates
- Semi-Markov chains and hidden semi-Markov models toward applications. Their use in reliability and DNA analysis.
- Stylized facts of financial time series and hidden semi-Markov models
- Hazard rate estimation under dependence conditions
- Functional density estimation of the transition operator of a discrete-time Markov process.
- Smoothed nonparametric estimation in window censored semi-Markov processes
- Nonparametric reliability estimation of semi-Markov processes
- Kernel estimators for semi-Markov processes
- Distributions associated with \((k_1,k_2)\) events on semi-Markov binary trials
- Estimation of the transition distributions of a Markov renewal process
- Regenerative stochastic processes
- Semi-Markov models for partially censored data
- Non-parametric estimation for semi-Markov kernels with application to reliability analysis
- Multistage plug—in bandwidth selection for kernel distribution function estimates
- Probability: A Graduate Course
- Empirical estimation for discrete-time semi-Markov processes with applications in reliability
- Limit Theorems for Markov Renewal Processes
- Some New Estimates for Distribution Functions
- Markov Renewal Processes with Finitely Many States
- Markov renewal theory
- Markov Renewal Processes: Definitions and Preliminary Properties
- Minimum divergence estimators for the Radon–Nikodym derivatives of the semi-Markov kernel
- On the consistency of a kernel estimator of the distribution density of the sojourn time in a fixed state for semi-Markov processes.
- Semi-Markov processes and reliability
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