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Approximate Bayesian Computation with Missing Data

Approximate Bayesian Computation with missing data extends the likelihood-free ABC framework to settings where observations are incomplete or partially recorded. By simulating data under a posited model and accepting parameter draws whose simulated summary statistics are close to the observed ones, it bypasses the need to evaluate an intractable likelihood — even when some data values are absent.

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Taxonomisk metodpost · bayesian / bayesian

Beaumont, M. A., Zhang, W. & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. · URL
Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. John Wiley & Sons. · ISBN 978-0471655749

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See alsoApproximate Bayesian Computationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Inference with Missing Datamachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMCMC with missing datamachine-suggested · Relational suggestion, not evidence.See alsoMultiple Imputationmachine-suggested · Relational suggestion, not evidence.Same method familyParticle Filtermachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSequential Monte Carlomachine-suggested · Relational suggestion, not evidence.