Approximate Bayesian Computation: Bayesian inference, Posterior probability, Dynamical system, Prior probability, Sufficient statistic, Markov chain Monte Carlo, Particle filter - Brossura

 
9786133779914: Approximate Bayesian Computation: Bayesian inference, Posterior probability, Dynamical system, Prior probability, Sufficient statistic, Markov chain Monte Carlo, Particle filter

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Approximate Bayesian computation (ABC) is a family of computational techniques in Bayesian statistics. These simulation techniques operate on summary data (such as population mean, or variance) to make broad inferences with less computation than might be required if all available data were analyzed in detail. They are especially useful in situations where evaluation of the likelihood is computationally prohibitive, or whenever suitable likelihoods are not available.

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