An MCMC computational approach for a continuous time state-dependent regime switching diffusion process-Reference-Cited by-同舟云学术

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An MCMC computational approach for a continuous time state-dependent regime switching diffusion process

Published:2019-10-16 Issue:8 Volume:47 Page:1354-1374
ISSN:0266-4763
Container-title:Journal of Applied Statistics
language:en
Short-container-title:Journal of Applied Statistics

Author:

Hibbah El Houcine¹^ORCID,El Maroufy Hamid¹^ORCID,Fuchs Christiane²³⁴^ORCID,Ziad Taib⁵⁶^ORCID

Affiliation:

1. Department of Applied Mathematics, Faculty of Sciences and Technics, Sultan Mouly Slimane University, Morocco

2. Faculty of Business Administration and Economics, Bielefeld University, Bielefield, Germany

3. Helmholtz Zentrum Munchen, German Research Center for Environmental Health GmbH, Institute of Computational Biology, Neuherberg, Germany

4. Chair of Mathematical Modeling of Biology Systems, Technisché Universität München, Garching, Germany

5. Faculty of Mathematics, Chalmers University of Technology, Göteborg, Sweden

6. Statistical Science Director at Astrazeneca, Sweden

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/02664763.2019.1677573

Reference44 articles.

1. An option pricing formula for the GARCH diffusion model

2. Testing Continuous-Time Models of the Spot Interest Rate

3. A bivariate markov process with diffusion and discrete components

4. Random diffusion models for animal movement

5. Bayesian inference for Markov processes with diffusion and discrete components

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1. Switching diffusions for multiscale uncertainty quantification;International Journal of Non-Linear Mechanics;2024-10

2. Estimation of regime-switching diffusions via Fourier transforms;Statistics and Computing;2024-03-05

3. MCMC analysis for a continuous time hidden Markov autoregressive process in disease progression;AIP Conference Proceedings;2024

4. An analysis of East African tea crop prices using the MCMC approach to estimate volatility and forecast the in-sample value-at-risk;Scientific African;2023-03

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