The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Bayesian Computation and Model Selection Without Likelihoods
Open accessAbstract
Until recently, the use of Bayesian inference was limited to a few cases because for many realistic probability models the likelihood function cannot be calculated analytically. The situation changed with the advent of likelihood-free inference algorithms, often subsumed under the term approximate Bayesian computation (ABC). A key innovation was the use of a postsampling regression adjustment, allowing larger tolerance values and as such shifting computation time to realistic orders of magnitude. Here we propose a reformulation of the regression adjustment in terms of a general linear model (GLM). This allows the integration into the sound theoretical framework of Bayesian statistics and the use of its methods, including model selection via Bayes factors. We then apply the proposed methodology to the question of population subdivision among western chimpanzees, Pan troglodytes verus.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The limitations that have been highlighted in the literature are pertinent for cases where inferences are based on summary statistics of the data instead of the data themselves, an approach conventionally adopted in population genetics applications. In these cases model selection is notoriously dependent on arbitrary choices made in the set-up of the ABC inference, and can swing in favor of any Pl”
From A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation (2014) · cites this paper as [61]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Arlequin (version 3.0): An integrated software package for population genetics data analysis
Excoffier, L., Laval, G., & Schneider, S. (2005) · Evolutionary Bioinformatics · doi:10.1177/117693430500100003 · Cited by 14,265
On the number of segregating sites in genetical models without recombination
Watterson, G. A. (1975) · Theoretical Population Biology · doi:10.1016/0040-5809(75)90020-9 · Cited by 3,933
Approximate Bayesian computation in population genetics
Beaumont, M. A., Zhang, W., & Balding, D. J. (2002) · Genetics · doi:10.1093/genetics/162.4.2025 · Cited by 2,932
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
An Introduction to Bayesian Inference in Econometrics.
Sargan, J. D., & Zellner, A. (1974) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344559 · Cited by 1,938
Markov chain Monte Carlo without likelihoods
Marjoram, P., Molitor, J., Plagnol, V., & Tavaré, S. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0306899100 · Cited by 1,199
Inferring Coalescence Times From DNA Sequence Data
Tavaré, S., Balding, D. J., Griffiths, R., & Donnelly, P. (1997) · Genetics · doi:10.1093/genetics/145.2.505 · Cited by 941
Sequential Monte Carlo without likelihoods
Sisson, S. A., Fan, Y., & Tanaka, M. M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0607208104 · Cited by 859
Adaptive approximate Bayesian computation
Beaumont, M. A., Cornuet, J.-M., Marin, J.-M., & Robert, C. P. (2009) · Biometrika · doi:10.1093/biomet/asp052 · Cited by 614
An Introduction to Bayesian Inference in Econometrics
Good, I. J. (1975) · Technometrics · doi:10.1080/00401706.1975.10489285 · Cited by 452
Research works printed but not linked: 5
- 2007, Genome Res., 17, 1505, 10.1101/gr.6409707 · DOI
- 2005, Evol. Bioinform. Online, 1, 47
- 2006, Proc. Natl. Acad. Sci. USA, 102, 7476
- 2006, Nat. Rev. Genet., 10, 759
- 2005, Mol. Biol. Evol., 22, 297
Cited by
Sorted by citations
Robust Demographic Inference from Genomic and SNP Data
Excoffier, L., Dupanloup, I., Huerta‐Sánchez, E., Sousa, V. C., & Foll, M. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003905 · Cited by 1,480
Approximate Bayesian Computation (ABC) in practice
Csilléry, K., Blum, M. G. B., Gaggiotti, O. E., & François, O. (2010) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2010.04.001 · Cited by 1,302
Approximate Bayesian Computation in Evolution and Ecology
Beaumont, M. (2010) · Annual Review of Ecology Evolution and Systematics · doi:10.1146/annurev-ecolsys-102209-144621 · Cited by 1,117
Huang, W., Takebayashi, N., Qi, Y., & Hickerson, M. J. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-1 · Cited by 952
Approximate Bayesian computational methods
Marin, J., Pudlo, P., Robert, C. P., & Ryder, R. (2011) · Statistics and Computing · doi:10.1007/s11222-011-9288-2 · Cited by 822
Approximate Bayesian Computation
Sunnåker, M., Busetto, A. G., Numminen, E., Corander, J., Foll, M., & Dessimoz, C. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002803 · Cited by 636
Cornuet, J., Ravigné, V., & Estoup, A. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-401 · Cited by 475
ABC as a flexible framework to estimate demography over space and time: some cons, many pros
Bertorelle, G., Benazzo, A., & Mona, S. (2010) · Molecular Ecology · doi:10.1111/j.1365-294x.2010.04690.x · Cited by 465
ABCtoolbox: a versatile toolkit for approximate Bayesian computations
Wegmann, D., Leuenberger, C., Neuenschwander, S., & Excoffier, L. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-116 · Cited by 407
Self-citationBayesian inference analyses of the polygenic architecture of rheumatoid arthritis
Diabetes Genetics Replication and Meta-analysis Consortium, Stahl, E. A., Myocardial Infarction Genetics Consortium, Wegmann, D., Trynka, G., Gutierrez-Achury, J., Do, R., Voight, B. F., Kraft, P., Chen, R., et al. (2012) · Nature Genetics · doi:10.1038/ng.2232 · Cited by 388
Self-citationStatistical inference for stochastic simulation models - theory and application
Hartig, F., Calabrese, J. M., Reineking, B., Wiegand, T., & Huth, A. (2011) · Ecology Letters · doi:10.1111/j.1461-0248.2011.01640.x · Cited by 384
A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation
Blum, M. G. B., Nunes, M. A., Prangle, D., & Sisson, S. A. (2013) · Statistical Science · doi:10.1214/12-sts406 · Cited by 355
Frantz, L., Schraiber, J. G., Madsen, O., Megens, H., Cagan, A., Bosse, M., Paudel, Y., Crooijmans, R. P. M. A., Larson, G., & Groenen, M. A. M. (2015) · Nature Genetics · doi:10.1038/ng.3394 · Cited by 342
Lack of confidence in approximate Bayesian computation model choice
Robert, C. P., Cornuet, J.-M., Marin, J.-M., & Pillai, N. S. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1102900108 · Cited by 317
Morphometric, Behavioral, and Genomic Evidence for a New Orangutan Species
Nater, A., Mattle‐Greminger, M. P., Nurcahyo, A., Nowak, M. G., de Manuel, M., Desai, T., Groves, C. P., Pybus, M., Sonay, T. B., Roos, C., et al. (2017) · Current Biology · doi:10.1016/j.cub.2017.09.047 · Cited by 328
A tutorial on approximate Bayesian computation
Turner, B. M., & Zandt, T. V. (2012) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2012.02.005 · Cited by 294
Ecological niche models in phylogeographic studies: applications, advances and precautions
Alvarado‐Serrano, D. F., & Knowles, L. L. (2013) · Molecular Ecology Resources · doi:10.1111/1755-0998.12184 · Cited by 281
Fundamentals and Recent Developments in Approximate Bayesian Computation
Lintusaari, J., Gutmann, M. U., Dutta, R., Samuel Kaski, A., & Corander, J. (2016) · Systematic Biology · doi:10.1093/sysbio/syw077 · Cited by 220
Liepe, J., Kirk, P., Filippi, S., Toni, T., Barnes, C. P., & Stumpf, M. P. H. (2014) · Nature Protocols · doi:10.1038/nprot.2014.025 · Cited by 217
Bayesian computation: a summary of the current state, and samples backwards and forwards
Green, P., Łatuszyński, K., Pereyra, M., & Robert, C. (2015) · Statistics and computing · doi:10.1007/s11222-015-9574-5 · Cited by 202
Distinguishing between selective sweeps from standing variation and from a de novo mutation
Peter, B. M., Huerta-Sanchez, E., & Nielsen, R. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1003011 · Cited by 193
In defence of model-based inference in phylogeography
Beaumont, M., Nielsen, R., Robert, C. P., Hey, J., Gaggiotti, O. E., Knowles, L. L., Estoup, A., Panchal, M., Corander, J., Hickerson, M., et al. (2010) · Molecular Ecology · doi:10.1111/j.1365-294x.2009.04515.x · Cited by 197
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive FlowsPreprint
Papamakarios, G., Sterratt, D. C., & Murray, I. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.07226 · Cited by 190
PARALLEL EVOLUTION OF LOCAL ADAPTATION AND REPRODUCTIVE ISOLATION IN THE FACE OF GENE FLOW
Butlin, R. K., Saura, M., Charrier, G., Jackson, B., André, C., Caballero, A., Coyne, J. A., Galindo, J., Grahame, J., Hollander, J., et al. (2013) · Evolution · doi:10.1111/evo.12329 · Cited by 197
Approximate Bayesian Computation
Beaumont, M. (2018) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-030718-105212 · Cited by 185
Almathen, F. S., Charruau, P., Mohandesan, E., Mwacharo, J. M., Orozco‐terWengel, P., Pitt, D., Abdussamad, A. M., Uerpmann, M., Uerpmann, H., Cupere, B. D., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1519508113 · Cited by 166
Veeramah, K. R., Wegmann, D., Woerner, A. E., Mendez, F. L., Watkins, J. C., Destro‐Bisol, G., Soodyall, H., Louie, L. G., & Hammer, M. F. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr212 · Cited by 139
Self-citationNetwork Models: An Underutilized Tool in Wildlife Epidemiology?
Craft, M. E., & Caillaud, D. (2011) · Interdisciplinary Perspectives on Infectious Diseases · doi:10.1155/2011/676949 · Cited by 138
Tsutaya, T., & Yoneda, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072327 · Cited by 133
He, Q., Edwards, D. L., & Knowles, L. L. (2013) · Evolution · doi:10.1111/evo.12159 · Cited by 130
Nadachowska‐Brzyska, K., Burri, R., Olason, P. I., Kawakami, T., Smeds, L., & Ellegren, H. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003942 · Cited by 127
Peter, B. M., Wegmann, D., & Excoffier, L. (2010) · Molecular Ecology · doi:10.1111/j.1365-294x.2010.04783.x · Cited by 124
Self-citationResolving Evolutionary Relationships in Closely Related Species with Whole-Genome Sequencing Data
Nater, A., Burri, R., Kawakami, T., Smeds, L., & Ellegren, H. (2015) · Systematic Biology · doi:10.1093/sysbio/syv045 · Cited by 119
Isolation and gene flow: inferring the speciation history of European house mice
Duvaux, L., Belkhir, K., Boulesteix, M., & Boursot, P. (2011) · Molecular Ecology · doi:10.1111/j.1365-294x.2011.05343.x · Cited by 116
Bayesian Inference of the Demographic History of Chimpanzees
Wegmann, D., & Excoffier, L. (2010) · Molecular Biology and Evolution · doi:10.1093/molbev/msq028 · Cited by 116
Self-citationThe population genomics of plant adaptation
Siol, M., Wright, S., & Barrett, S. C. H. (2010) · New Phytologist · doi:10.1111/j.1469-8137.2010.03401.x · Cited by 123
Estoup, A., Lombaert, É., Marin, J., Guillemaud, T., Pudlo, P., Robert, C. P., & Cornuet, J. (2012) · Molecular Ecology Resources · doi:10.1111/j.1755-0998.2012.03153.x · Cited by 115
Demographic factors shaped diversity in the two gene pools of wild common bean Phaseolus vulgaris L.
Mamidi, S., Rossi, M., Moghaddam, S. M., Annam, D., Lee, R., Papa, R., & McClean, P. E. (2012) · Heredity · doi:10.1038/hdy.2012.82 · Cited by 114
Inferring responses to climate dynamics from historical demography in neotropical forest lizards
Prates, I., Xue, A. T., Brown, J. L., Alvarado‐Serrano, D. F., Rodrigues, M. T., Hickerson, M. J., & Carnaval, A. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601063113 · Cited by 114
A Novel Approach for Choosing Summary Statistics in Approximate Bayesian Computation
Aeschbacher, S., Beaumont, M., & Futschik, A. (2012) · Genetics · doi:10.1534/genetics.112.143164 · Cited by 111
The history and evolution of the Denisovan- EPAS1 haplotype in Tibetans
Zhang, X., Witt, K. E., Bañuelos, M. M., Ko, A., Yuan, K., Xu, S., Nielsen, R., & Huerta-Sanchez, E. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2020803118 · Cited by 105
Using Ancient DNA to Understand Evolutionary and Ecological Processes
Orlando, L., & Cooper, A. (2014) · Annual Review of Ecology Evolution and Systematics · doi:10.1146/annurev-ecolsys-120213-091712 · Cited by 104
Mamidi, S., Rossi, M., Annam, D., Moghaddam, S. M., Lee, R., Papa, R., & McClean, P. E. (2011) · Functional Plant Biology · doi:10.1071/fp11124 · Cited by 102
Drosophila suzukii: The Genetic Footprint of a Recent, Worldwide Invasion
Adrion, J. R., Kousathanas, A., Pascual, M., Burrack, H. J., Haddad, N. M., Bergland, A. O., Machado, H. E., Sackton, T. B., Schlenke, T. A., Watada, M., et al. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu246 · Cited by 95
Self-citationPaternal Origins and Migratory Episodes of Domestic Sheep
Deng, J., Xie, X.-L., Wang, D.-F., Zhao, C., Lv, F., Li, X., Yang, J. H., Yu, J.-L., Shen, M., Gao, L., et al. (2020) · Current Biology · doi:10.1016/j.cub.2020.07.077 · Cited by 99
Slater, G. J., Harmon, L. J., Wegmann, D., Joyce, P., Revell, L. J., & Alfaro, M. E. (2011) · Evolution · doi:10.1111/j.1558-5646.2011.01474.x · Cited by 82
Self-citationBrown, J. L., & Knowles, L. L. (2012) · Molecular Ecology · doi:10.1111/j.1365-294x.2012.05640.x · Cited by 79
Cornille, A., Giraud, T., Bellard, C., Tellier, A., Cam, B. L., SMULDERS, M. J. M., Kleinschmit, J. R. G., Roldán-Ruíz, I., & Gladieux, P. (2013) · Molecular Ecology · doi:10.1111/mec.12231 · Cited by 76
Climate change and human colonization triggered habitat loss and fragmentation in Madagascar
Salmona, J., Heller, R., Quéméré, E., & Chikhi, L. (2017) · Molecular Ecology · doi:10.1111/mec.14173 · Cited by 79
A simulated annealing approach to approximate Bayes computations
Albert, C., Künsch, H. R., & Scheidegger, A. (2014) · Statistics and Computing · doi:10.1007/s11222-014-9507-8 · Cited by 74
Oaks, J. R., Sukumaran, J., Esselstyn, J. A., Linkem, C. W., Siler, C. D., Holder, M. T., & Brown, R. M. (2012) · Evolution · doi:10.1111/j.1558-5646.2012.01840.x · Cited by 71
Estoup, A., Baird, S. J. E., Ray, N., Currat, M., Cornuet, J., Santos, F., Beaumont, M., & Excoffier, L. (2010) · Molecular Ecology Resources · doi:10.1111/j.1755-0998.2010.02882.x · Cited by 67
Oliveira, S., Fehn, A., Aço, T., Lages, F., Gayà‐Vidal, M., Pakendorf, B., Stoneking, M., & Rocha, J. (2018) · American Journal of Physical Anthropology · doi:10.1002/ajpa.23378 · Cited by 64
Massatti, R. T., & Knowles, L. L. (2016) · Molecular Ecology · doi:10.1111/mec.13735 · Cited by 62
Isolation and gene flow in a speciation continuum in newts
Pabijan, M., Zieliński, P., Dudek, K., Stuglik, M., & Babik, W. (2017) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2017.08.003 · Cited by 59
Use of Bayesian statistics in drug development: Advantages and challenges
Gupta, S. K. (2012) · International Journal of Applied and Basic Medical Research · doi:10.4103/2229-516x.96789 · Cited by 60
Caillaud, D., Crofoot, M. C., Scarpino, S. V., Jansen, P. A., Garzón‐López, C. X., Winkelhagen, A. J. S., Bohlman, S., & Walsh, P. D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015002 · Cited by 59
Knowles, L. L., & Massatti, R. T. (2016) · Ecography · doi:10.1111/ecog.02893 · Cited by 58
Historical sampling reveals dramatic demographic changes in western gorilla populations
Thalmann, O., Wegmann, D., Spitzner, M., Arandjelovic, M., Guschanski, K., Leuenberger, C., Bergl, R. A., & Vigilant, L. (2011) · BMC Evolutionary Biology · doi:10.1186/1471-2148-11-85 · Cited by 56
Self-citationGratton, P., Allegrucci, G., Sbordoni, V., & Gandolfi, A. (2014) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2014.06.022 · Cited by 54
Demographic history of a recent invasion of house mice on the isolated I sland of G ough
GRAY, M. M., Wegmann, D., Haasl, R. J., White, M. A., Gabriel, S. I., Searle, J. B., Cuthbert, R., Ryan, P. G., & Payseur, B. A. (2014) · Molecular Ecology · doi:10.1111/mec.12715 · Cited by 55
Self-citationApproximate Bayesian computation via regression density estimation
Fan, Y., Nott, D. J., & Sisson, S. A. (2013) · Stat · doi:10.1002/sta4.15 · Cited by 54
Veeramah, K. R., Woerner, A. E., Johnstone, L. M., Gut, I. G., Gut, M. O., Marquès‐Bonet, T., Carbone, L., Wall, J. D., & Hammer, M. F. (2015) · Genetics · doi:10.1534/genetics.115.174425 · Cited by 55
Brown, J. L., Weber, J. J., Alvarado‐Serrano, D. F., Hickerson, M. J., Franks, S. J., & Carnaval, A. C. (2016) · American Journal of Botany · doi:10.3732/ajb.1500117 · Cited by 53
Genomic evidence of survival near ice sheet margins for some, but not all, North American trees
Bemmels, J. B., Knowles, L. L., & Dick, C. W. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1901656116 · Cited by 50
Elleouet, J. S., & Aitken, S. N. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12758 · Cited by 50
Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia
Alves, I., Arenas, M., Currat, M., Hanulová, A. Š., Sousa, V. C., Ray, N., & Excoffier, L. (2015) · Molecular Biology and Evolution · doi:10.1093/molbev/msv332 · Cited by 50
Approximate Bayesian Computation and Bayes’ Linear Analysis: Toward High-Dimensional ABC
Nott, D. J., Fan, Y., Marshall, L. A., & Sisson, S. A. (2012) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2012.751874 · Cited by 47
Leduc, A., Traoré, Y. N., Boyer, K., Magne, M., Grygiel, P., Juhász, C., Boyer, C., Guérin, F., Wonni, I., Ouedraogo, L., et al. (2015) · Environmental Microbiology · doi:10.1111/1462-2920.12876 · Cited by 46
Independent domestications of cultivated tree peonies from different wild peony species
Yuan, J., Cornille, A., Giraud, T., Cheng, F., & Hu, Y. (2013) · Molecular Ecology · doi:10.1111/mec.12567 · Cited by 46
Pérez-Pardal, L., Sánchez-Gracia, A., Álvarez, I., Traoré, A., Ferraz, J. B. S., Fernández, I., Costa, V., Chen, S., Tapio, M., Cantet, R. J. C., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-36444-7 · Cited by 45
Deviance Information Criteria for Model Selection in Approximate Bayesian Computation
François, O., & Laval, G. (2011) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1678 · Cited by 44
Marginal Likelihoods in Phylogenetics: A Review of Methods and Applications
Oaks, J. R., Cobb, K. A., Minin, V. N., & Leaché, A. D. (2019) · Systematic Biology · doi:10.1093/sysbio/syz003 · Cited by 43
Álvarez‐Presas, M., Sánchez‐Gracia, A., Carbayo, F., Rozas, J., & Riutort, M. (2014) · Heredity · doi:10.1038/hdy.2014.3 · Cited by 42
Jaatha: a fast composite-likelihood approach to estimate demographic parameters
Naduvilezhath, L., ROSE, L. E., & Metzler, D. (2011) · Molecular Ecology · doi:10.1111/j.1365-294x.2011.05131.x · Cited by 41
Bidegaray‐Batista, L., Sánchez‐Gracia, A., Santulli, G., Maiorano, L., Guisan, A., Vogler, A. P., & Arnedo, M. A. (2016) · Molecular Ecology · doi:10.1111/mec.13585 · Cited by 41
Dussex, N., Wegmann, D., & Robertson, B. C. (2014) · Molecular Ecology · doi:10.1111/mec.12729 · Cited by 39
Self-citationReconstructing the demographic history of orang‐utans using Approximate B ayesian Computation
Nater, A., Greminger, M. P., Arora, N., van Schaik, C. P., Goossens, B., Singleton, I., Verschoor, E. J., Warren, K. S., & Krützen, M. (2014) · Molecular Ecology · doi:10.1111/mec.13027 · Cited by 38
Bemmels, J. B., Title, P. O., Ortego, J., & Knowles, L. L. (2016) · Molecular Ecology · doi:10.1111/mec.13804 · Cited by 38
Theodoridis, S., Randin, C. F., Szövényi, P., Boucher, F. C., Patsiou, T., & Conti, E. (2016) · Systematic Biology · doi:10.1093/sysbio/syw114 · Cited by 39
Mardulyn, P., Goffredo, M., Conte, A., Hendrickx, G., Meiswinkel, R., Balenghien, T., Sghaier, S., Lohr, Y., & Gilbert, M. (2013) · Molecular Ecology · doi:10.1111/mec.12264 · Cited by 36
Likelihood-Free Inference by Ratio Estimation
Thomas, O., Dutta, R., Corander, J., Samuel Kaski, A., & Gutmann, M. U. (2020) · Bayesian Analysis · doi:10.1214/20-ba1238 · Cited by 36
Antoniazza, S., Kanitz, R., Neuenschwander, S., Burri, R., Gaigher, A., Roulin, A., & Goudet, J. (2014) · Molecular Ecology · doi:10.1111/mec.12957 · Cited by 35
Neural Density Estimation and Likelihood-free InferencePreprint
Papamakarios, G. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1910.13233 · Cited by 78
Pan, D., Hülber, K., Willner, W., & Schneeweiss, G. M. (2019) · Molecular Ecology · doi:10.1111/mec.15316 · Cited by 33
Candidate Targets of Balancing Selection in the Genome of Staphylococcus aureus
Thomas, J. C., Godfrey, P. A., Feldgarden, M., & Robinson, D. A. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr286 · Cited by 32
A test for ancient selective sweeps and an application to candidate sites in modern humans
Racimo, F., Kuhlwilm, M., & Slatkin, M. (2014) · Molecular Biology and Evolution · doi:10.1093/molbev/msu255 · Cited by 30
Model Selection in Historical Research Using Approximate Bayesian Computation
Rubio‐Campillo, X. (2016) · PLoS ONE · doi:10.1371/journal.pone.0146491 · Cited by 31
Genetic analyses favour an ancient and natural origin of elephants on Borneo
Sharma, R., Goossens, B., Heller, R., Rasteiro, R., Othman, N., Bruford, M. W., & Chikhi, L. (2018) · Scientific Reports · doi:10.1038/s41598-017-17042-5 · Cited by 31
An improved approximate-Bayesian model-choice method for estimating shared evolutionary history
Oaks, J. R. (2014) · BMC Evolutionary Biology · doi:10.1186/1471-2148-14-150 · Cited by 29
SIMULATION-BASED LIKELIHOOD APPROACH FOR EVOLUTIONARY MODELS OF PHENOTYPIC TRAITS ON PHYLOGENY
Kutsukake, N., & Innan, H. (2012) · Evolution · doi:10.1111/j.1558-5646.2012.01775.x · Cited by 27
Dı́az, F., Lima, A. L. A., Nakamura, A. M., Fernandes, F., Sobrinho, I. S., & de Brito, R. A. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00359 · Cited by 27
Tonzo, V., & Ortego, J. (2021) · Diversity and Distributions · doi:10.1111/ddi.13306 · Cited by 26
Likelihood-free parallel tempering
Baragatti, M. C., Grimaud, A., & Pommeret, D. (2012) · Statistics and Computing · doi:10.1007/s11222-012-9328-6 · Cited by 26
Ortego, J., & Knowles, L. L. (2020) · Molecular Ecology · doi:10.1111/mec.15548 · Cited by 25
Dong, F., Hung, C., & Yang, X. (2019) · Molecular Phylogenetics and Evolution · doi:10.1016/j.ympev.2019.106671 · Cited by 25
Di, D., Sanchez‐Mazas, A., & Currat, M. (2015) · BMC Evolutionary Biology · doi:10.1186/s12862-015-0512-0 · Cited by 24
Likelihood-Free Inference in High-Dimensional Models
Kousathanas, A., Leuenberger, C., Helfer, J., Quinodoz, M., Foll, M., & Wegmann, D. (2016) · Genetics · doi:10.1534/genetics.116.187567 · Cited by 22
Self-citationGuirao‐Rico, S., Sánchez‐Gracia, A., & Charlesworth, D. (2016) · Molecular Ecology · doi:10.1111/mec.13969 · Cited by 21
DeepDive: estimating global biodiversity patterns through time using deep learning
Cooper, R. B., Flannery‐Sutherland, J. T., & Silvestro, D. (2024) · Nature Communications · doi:10.1038/s41467-024-48434-7 · Cited by 25
Metadata
- Authors
- Leuenberger, C., & Wegmann, D.
- Affiliations
- University of Fribourg (CH)
- University of Bern (CH)
- Corresponding author
- Leuenberger, Christoph
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-01-01
- Volume
- 184
- Issue
- 1
- Pages
- 243-252
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- PMC
- PMC2815920
- OpenAlex
- W2118659960
- Cited by
- 175
- References
- 23
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2022: 2 · 2021: 3 · 2020: 7 · 2019: 15 · 2018: 13 · 2017: 6 · 2016: 17 · 2015: 14 · 2014: 22 · 2013: 19 · 2012: 13
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Genetics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- reroDoc Digital Library (submittedVersion)
- BORIS (University Library Bern) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- approximate Bayesian computation, simulation-based inference, regression adjustment, general linear model, model selection, Bayes factor, population subdivision, western chimpanzee, Pan troglodytes verus, population genetics
- MeSH terms
- Algorithms, Animals, Bayes Theorem, Pan troglodytes, Genetics, Population, Humans, Models, Genetic, Likelihood Functions, Linear Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review