Fundamentals and Recent Developments in Approximate Bayesian Computation

Show full item record



Permalink

http://hdl.handle.net/10138/312716

Citation

Lintusaari , J , Gutmann , M U , Dutta , R , Kaski , S & Corander , J 2017 , ' Fundamentals and Recent Developments in Approximate Bayesian Computation ' , Systematic Biology , vol. 66 , no. 1 , pp. E66-E82 . https://doi.org/10.1093/sysbio/syw077

Title: Fundamentals and Recent Developments in Approximate Bayesian Computation
Author: Lintusaari, Jarno; Gutmann, Michael U.; Dutta, Ritabrata; Kaski, Samuel; Corander, Jukka
Contributor organization: Helsinki Institute for Information Technology
Department of Mathematics and Statistics
Jukka Corander / Principal Investigator
Date: 2017-01
Language: eng
Number of pages: 17
Belongs to series: Systematic Biology
ISSN: 1063-5157
DOI: https://doi.org/10.1093/sysbio/syw077
URI: http://hdl.handle.net/10138/312716
Abstract: Bayesian inference plays an important role in phylogenetics, evolutionary biology, and in many other branches of science. It provides a principled framework for dealing with uncertainty and quantifying how it changes in the light of new evidence. For many complex models and inference problems, however, only approximate quantitative answers are obtainable. Approximate Bayesian computation (ABC) refers to a family of algorithms for approximate inference that makes a minimal set of assumptions by only requiring that sampling from a model is possible. We explain here the fundamentals of ABC, review the classical algorithms, and highlight recent developments.
Subject: ABC
approximate Bayesian computation
Bayesian inference
likelihood-free inference
phylogenetics
simulator-based models
stochastic simulation models
tree-based models
MONTE-CARLO
INDIRECT INFERENCE
MODEL SELECTION
EVOLUTION
LIKELIHOODS
SYSTEMS
STATISTICS
PARAMETERS
1181 Ecology, evolutionary biology
112 Statistics and probability
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


Files in this item

Total number of downloads: Loading...

Files Size Format View
syw077.pdf 1.135Mb PDF View/Open

This item appears in the following Collection(s)

Show full item record