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- W2297145956 abstract "This letter revisits a recent result for the score function estimation by making use of a basic property of the convolution operator. With a probabilistic view of the convolution property, the score function can be estimated as a function of the mean of the parameter posterior distribution, when a pseudoprior distribution for the parameter is introduced. In this letter, the pseudoprior for the parameter is assumed to be Gaussian, which is a common choice in practice. In the end, a toy numerical experiment is implemented to show the efficacy of the estimator, where a particle Markov chain Monte Carlo (MCMC) method is used to sample from the parameter posterior distribution." @default.
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- W2297145956 date "2016-04-01" @default.
- W2297145956 modified "2023-09-24" @default.
- W2297145956 title "Using Convolution to Estimate the Score Function for Intractable State-Transition Models" @default.
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- W2297145956 doi "https://doi.org/10.1109/lsp.2016.2526667" @default.
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