Approximate Bayesian computation: Difference between revisions

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'''Approximate Bayesian computation''' (ABC) is a family of computational techniquetechniques 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.

==See also==

[[Markov chain Monte Carlo]]

==References==

*{{cite journal|last = Pritchard|first = J. K.|coauthors = Seielstad, M. T., Perez-Lezaun, A., and Feldman, M. T.|title = Population Growth of Human Y Chromosomes: A Study of Y Chromosome Microsatellites|journal = Mol. Biol. Evol.|volume = 16|date = 1999|pages = 1791-1798}}

*{{cite journal|last = Beaumont|first = M. A.|coauthors = Zhang, W. and Balding, D. J.|title = Approximate Bayesian Computation in Population Genetics|journal = Genetics|volume = 162|date = Dec 2002|pages = 2025-2035|url = http://www.genetics.org/cgi/content/abstract/162/4/2025}}

*{{cite journal|last = Plagnol|first = V.|coauthors = Tavaré, S.|title = Approximate Bayesian computation and MCMC|journal = Monte Carlo and Quasi-Monte Carlo Methods 2002|year = 2004|url = http://www-gene.cimr.cam.ac.uk/vplagnol/papers/vpst-web.pdf}} (The link is to a preprint.)

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