‘ABC Bayes’ directory
- See Also
- Gwern
- Links
- “Genetic Adaptation to Pathogens and Increased Risk of Inflammatory Disorders in Post-Neolithic Europe”, Kerner et al 2022
- “Gene-Drive Suppression of Mosquito Populations in Large Cages As a Bridge between Lab and Field”, Hammond et al 2021
- “A Genome-Wide Approximate Bayesian Computation Approach Suggests Only Limited Numbers of Soft Sweeps in Humans over the Last 100,000 Years”, Laval et al 2019
- “Approximate Bayesian Computation [Review]”, Beaumont 2019
- “The Bayesian Superorganism I: Collective Probability Estimation”, Hunt et al 2018
- “Mining Gold from Implicit Models to Improve Likelihood-Free Inference”, Brehmer et al 2018
- “Lack of Confidence in Approximate Bayesian Computation Model Choice”, Robert 2011
- “Experiments With the Site Frequency Spectrum”, Sainudiin et al 2010
- “Demographic History of European Populations of Arabidopsis Thaliana”, François et al 2008
- “Introduction History of Drosophila Subobscura in the New World: a Microsatellite-Based Survey Using ABC Methods”, Pascual et al 2007
- “Approximate Bayesian Computation in Population Genetics”, Beaumont et al 2002
- “Estimating the Age of the Common Ancestor of a Sample of DNA Sequences”
- “Population Growth of Human Y Chromosomes: a Study of Y Chromosome Microsatellites”
- “Introduction to Approximate Bayesian Computation (ABC)”
- “Multiple Transatlantic Introductions of the Western Corn Rootworm”
- “Approximate Bayesian Computation”, Sunnåker et al 2026
- “Approximate Bayesian Computation in Evolution and Ecology”
- “Genetic Analysis of Complex Demographic Scenarios: Spatially Expanding Populations of the Cane Toad, Bufo Marinus”
- “Likelihood-Free Estimation of Model Evidence”
- “Markov Chain Monte Carlo without Likelihoods”
- “Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman”
- Wikipedia (1)
- Miscellaneous
- Bibliography
See Also
Gwern
“Statistical Notes”, Gwern 2014
“When Should I Check The Mail?”, Gwern 2015
Links
“Genetic Adaptation to Pathogens and Increased Risk of Inflammatory Disorders in Post-Neolithic Europe”, Kerner et al 2022
“Gene-Drive Suppression of Mosquito Populations in Large Cages As a Bridge between Lab and Field”, Hammond et al 2021
Gene-drive suppression of mosquito populations in large cages as a bridge between lab and field
“A Genome-Wide Approximate Bayesian Computation Approach Suggests Only Limited Numbers of Soft Sweeps in Humans over the Last 100,000 Years”, Laval et al 2019
“Approximate Bayesian Computation [Review]”, Beaumont 2019
“The Bayesian Superorganism I: Collective Probability Estimation”, Hunt et al 2018
The Bayesian Superorganism I: collective probability estimation
“Mining Gold from Implicit Models to Improve Likelihood-Free Inference”, Brehmer et al 2018
Mining gold from implicit models to improve likelihood-free inference
“Lack of Confidence in Approximate Bayesian Computation Model Choice”, Robert 2011
Lack of confidence in approximate Bayesian computation model choice
“Experiments With the Site Frequency Spectrum”, Sainudiin et al 2010
“Demographic History of European Populations of Arabidopsis Thaliana”, François et al 2008
Demographic History of European Populations of Arabidopsis thaliana
“Introduction History of Drosophila Subobscura in the New World: a Microsatellite-Based Survey Using ABC Methods”, Pascual et al 2007
“Approximate Bayesian Computation in Population Genetics”, Beaumont et al 2002
“Estimating the Age of the Common Ancestor of a Sample of DNA Sequences”
Estimating the age of the common ancestor of a sample of DNA sequences :
“Population Growth of Human Y Chromosomes: a Study of Y Chromosome Microsatellites”
Population growth of human Y chromosomes: a study of Y chromosome microsatellites :
“Introduction to Approximate Bayesian Computation (ABC)”
“Multiple Transatlantic Introductions of the Western Corn Rootworm”
Multiple transatlantic introductions of the Western corn rootworm
“Approximate Bayesian Computation”, Sunnåker et al 2026
“Approximate Bayesian Computation in Evolution and Ecology”
“Genetic Analysis of Complex Demographic Scenarios: Spatially Expanding Populations of the Cane Toad, Bufo Marinus”
“Likelihood-Free Estimation of Model Evidence”
“Markov Chain Monte Carlo without Likelihoods”
“Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman”
Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman
Wikipedia (1)
Miscellaneous
Bibliography
2007-pascual.pdf: “Introduction History of Drosophila Subobscura in the New World: a Microsatellite-Based Survey Using ABC Methods”,https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002803: “Approximate Bayesian Computation”,