| EPSRC Reference: |
GR/S61577/01 |
| Title: |
Bayesian inference for discretely observed continuous-time processes |
| Principal Investigator: |
Roberts, Professor G O |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Mathematics and Statistics |
| Organisation: |
Lancaster University |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 February 2004 |
Ends: |
31 January 2007 |
Value (£): |
173,098
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| EPSRC Research Topic Classifications: |
| Statistics & Appl. Probability |
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| EPSRC Industrial Sector Classifications: |
| Communications |
Financial Services |
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Summary on Grant Application Form |
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Although it is often natural to model observed stochastic phenomena in continuous time, observed data is always discrete. Moreover, unlike the continuous-time likelihood, the likelihood of the discrete skeleton chain is very often unavailable. Where data is observed on a sufficiently fine grid of times, likelihood-based inference is straightforward since accurate approximations to the continuous-time likelihood are available. When data is not sufficiently fine, a Bayesian approach using MCMC requires the imputation of additional data. However, for many stochastic process models such as diffusions, this is not a routine application of data-augmentation since the dependence between missing data and volatility is arbitrary large leading to extremely poor convergence of the obvious algorithm. This project will develop methodology for effective data-augmentation for these models. Generic model types such as diffusion processes with parameterised families of drift and diffusion coefficients will be studied. However other more specific model types where data-augmentation encounters particular problems, will also be analysed, including CTAR models, jump-diffusion models, and stochastic volatility models. Substantial application areas in the analysis of audio signals and financial time series will be considered.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.lancs.ac.uk |