The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes.
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Publication:2040938
DOI10.1007/s11203-020-09224-2zbMath1469.62331arXiv1812.00260OpenAlexW3045843218MaRDI QIDQ2040938
Stefano Peluso, Andrea Arfè, Pietro Muliere
Publication date: 15 July 2021
Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1812.00260
Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09) Sums of independent random variables; random walks (60G50)
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Cites Work
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- Dirichlet process hidden Markov multiple change-point model
- Predictive construction of priors in Bayesian nonparametrics
- Reinforced urn processes for credit risk models
- Bayes estimation from a Markov renewal process
- Semi-Markov chains and hidden semi-Markov models toward applications. Their use in reliability and DNA analysis.
- A survey of random processes with reinforcement
- Stylized facts of financial time series and hidden semi-Markov models
- Ignorability and coarse data
- Polya trees and random distributions
- Beta-stacy processes and a generalization of the Pólya-Urn scheme
- Ferguson distributions via Polya urn schemes
- Tailfree and neutral random probabilities and their posterior distributions
- Urn schemes and reinforced random walks.
- Semiparametric multivariate and multiple change-point modeling
- Bayesian nonparametric estimation for reinforced Markov renewal processes
- Partially exchangeable processes indexed by the vertices of a \(k\)-tree constructed via reinforce\-ment
- A randomly reinforced urn
- A Bayesian analysis of some nonparametric problems
- Reinforced random processes in continuous time.
- Estimation with right-censored observations under a semi-Markov model
- Probability and Stochastics
- Semi-Markov Risk Models for Finance, Insurance and Reliability
- Bayesian Nonparametrics
- A Bayesian approach to inference about a change-point in a sequence of random variables
- Interacting reinforced-urn systems
- Fitting Semi‐Markov Models to Interval‐Censored Data with Unknown Initiation Times
- Hurricane Lifespan Modeling through a Semi‐Markov Parametric Approach
- Reinforced urns and the subdistribution beta‐Stacy process prior for competing risks analysis
- Discrete-Time Semi-Markov Model for Reliability and Survival Analysis
- Reliability and Risk
- Markov renewal theory
