Choosing summary statistics by least angle regression for approximate Bayesian computation

DOI10.1080/02664763.2015.1134447OpenAlexW2466477043WikidataQ61826129 ScholiaQ61826129MaRDI QIDQ5138152

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Publication date: 3 December 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10454/14801

zbMATH Keywords

population geneticsrecombinationlikelihood-free methodsmutationleast angle regression

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

ABC–CDE: Toward Approximate Bayesian Computation With Complex High-Dimensional Data and Limited Simulations

Uses Software

• pls
• lars
• ABCtoolbox
• ElemStatLearn
• abc
• msABC
• GLMSELECT

Cites Work

• Unnamed Item
• A comparative review of dimension reduction methods in approximate Bayesian computation
• Least angle regression. (With discussion)
• On optimal selection of summary statistics for approximate Bayesian computation
• Approximately Sufficient Statistics and Bayesian Computation
• HIV with contact tracing: a case study in approximate Bayesian computation
• Adaptive approximate Bayesian computation
• Constructing Summary Statistics for Approximate Bayesian Computation: Semi-Automatic Approximate Bayesian Computation
• A new approach to choose acceptance cutoff for approximate Bayesian computation
• Sequential Monte Carlo without likelihoods
• Handbook of Statistical Genetics

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