Fearnhead, Paul and Meligkotsidou, Loukia (2004) Exact filtering for partially-oberved continuous-time models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66 (3). pp. 771-789. ISSN 1369-7412Full text not available from this repository.
Summary. The forward–backward algorithm is an exact filtering algorithm which can efficiently calculate likelihoods, and which can be used to simulate from posterior distributions. Using a simple result which relates gamma random variables with different rates, we show how the forward–backward algorithm can be used to calculate the distribution of a sum of gamma random variables, and to simulate from their joint distribution given their sum. One application is to calculating the density of the time of a specific event in a Markov process, as this time is the sum of exponentially distributed interevent times. This enables us to apply the forward–backward algorithm to a range of new problems. We demonstrate our method on three problems: calculating likelihoods and simulating allele frequencies under a non-neutral population genetic model, analysing a stochastic epidemic model and simulating speciation times in phylogenetics.
|Journal or Publication Title:||Journal of the Royal Statistical Society: Series B (Statistical Methodology)|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Mathematics and Statistics|
|Deposited By:||Mrs Yaling Zhang|
|Deposited On:||12 Jun 2008 16:22|
|Last Modified:||24 Jan 2017 01:55|
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