On a Nonparametric Change Point Detection Model in Markovian Regimes
| Autor: | Ramsés H. Mena, Asael Fabian Martínez |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: |
Statistics and Probability
Mathematical optimization Applied Mathematics Nonparametric statistics Sampling (statistics) Markov process Change point detection Sample (statistics) Ornstein–Uhlenbeck process symbols.namesake Bayesian nonparametric symbols Partition (number theory) Statistical physics Two-parameter Poisson-Dirichlet process Diffusion (business) Ornstein-Uhlenbeck process Change detection Mathematics |
| Zdroj: | Bayesian Anal. 9, no. 4 (2014), 823-858 |
| Popis: | Change point detection models aim to determine the most probable grouping for a given sample indexed on an ordered set. For this purpose, we propose a methodology based on exchangeable partition probability functions, specifically on Pitman’s sampling formula. Emphasis will be given to the Markovian case, in particular for discretely observed Ornstein-Uhlenbeck diffusion processes. Some properties of the resulting model are explained and posterior results are obtained via a novel Markov chain Monte Carlo algorithm. |
| Databáze: | OpenAIRE |
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