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This Chapter, "Overview of Approximate Bayesian Computation", is to appear as the first chapter in the forthcoming Handbook of Approximate Bayesian Computation (2018).
The corpsucle problem: A mathematical study of a biometric problem
Wicksell, S. D. (1925) · 1925
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Modern techniques in data analysis
Tukey, J. W. (1977) · 1977
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Some properties of the Tukey g g and h h family of distributions
Martinez, J. and B. Iglewicz (1984) · 1984
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Summarizing shape numerically: the g g -and- h h distributions
Hoaglin, D. C. (1985) · 1985
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Multivariate Density Estimation: Theory, Practice and Visualisation
Scott, D. W. (1992) · 1992
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Sampling theory for neutral alleles in a varying environment
Griffiths, R. C. and S. Tavare (1994) · 1994
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Kernel Smoothing
Wand, M. P. and M. C. Jones (1995) · 1995
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Inferring coalescence times from DNA sequence data
Tavaré, S., D. J. Balding, R. C. Griffiths, and P. Donnelly (1997) · 1997
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Population growth of human y chromosomes: a study of y chromosome microsatellites
Pritchard, J. K., M. T. Seielstad, A. Perez-Lezaun, and M. W. Feldman (1999) · 1999
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Monte Carlo methods in Bayesian computation
Chen, M.-H., Q.-M. Shao, and J. G. Ibrahim (2000) · 2000
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Inference in molecular population genetics
Stephens, M. and P. Donnelly (2000) · 2000
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An Introduction to Statistical Modelling of Extreme Values
Coles, S. G. (2001) · 2001
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Sequential Monte Carlo methods in practice
Doucet, A., N. de Freitas, and N. Gordon (2001) · 2001
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The larges inclusions in a piece of steel
Anderson, C. W. and S. G. Coles (2002) · 2002
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Generating samples under a wright–fisher neutral model of genetic variation
Hudson, R. R. (2002) · 2002
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Weighted quantile-based estimation for a class of transformation distributions
Rayner, G. and H. MacGillivray (2002) · 2002
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Estimation of population growth or decline in genetically monitored populations
Beaumont, M. A. (2003) · 2003
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Project report
Maciuca, S. (2003) · 2003
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Stereology for Statisticians
Baddeley, A. and E. B. V. Jensen (2004) · 2004
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Importance sampling on coalescent histories. i
De Iorio, M. and R. C. Griffiths (2004) · 2004
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Gene genealogies, variation and evolution: a primer in coalescent theory
Hein, J., M. Schierup, and C. Wiuf (2004) · 2004
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Bayesian estimation of recent migration rates after a spatial expansion
Hamilton, G., M. Currat, N. Ray, G. Heckel, M. A. Beaumont, and L. Excoffier (2005) · 2005
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Sequential Monte Carlo samplers
Del Moral, P., A. Doucet, and A. Jasra (2006) · 2006
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Modern computational approaches for analysing molecular genetic variation data
Marjoram, P. and S. Tavaré (2006) · 2006
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An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants
M ø \o ller, J., A. N. Pettitt, R. Reeves, and K. Berthelsen (2006) · 2006
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Bayesian inference, Monte Carlo sampling and operational risk
Peters, G. W. and S. A. Sisson (2006) · 2006
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Using Approximate Bayesian Computation to estimate tuberculosis transmission parameters from genotype data
Tanaka, M. M., A. R. Francis, F. Luciani, and S. A. Sisson (2006) · 2006
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Inference for stereological extremes
Bortot, P., S. G. Coles, and S. A. Sisson (2007) · 2007
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Statistical evaluation of alternative models of human evolution
Fagundes, N. J. R., N. Ray, M. A. Beaumont, S. Neuenschwander, F. M. Salzano, S. L. Bonatto, and L. Excoffier (2007) · 2007
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Using likelihood-free inference to compare evolutionary dynamics of the protien networks of h. pylori and p. falciparum
Ratmann, O., O. Jorgensen, T. Hinkley, M. Stumpf, S. Richardson, and C. Wiuf (2007) · 2007
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Bayesian estimation of quantile distributions
Allingham, D. R., A. R. King, and K. L. Mengersen (2009) · 2009
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ABC likelihood-free methods for model choice in Gibbs random fields
Grelaud, A., C. P. Robert, J.-M. Marin, F. Rodolphe, and J.-F. Taly (2009) · 2009
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Inferring the parameters of the netural theory of biodiversity using phylogenetic information and implications for tropical forests
Jabot, F. and J. Chave (2009) · 2009
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The epidemiological fitness cost of drug resistance in Mycobacterium tuberculosis
Luciani, F., S. A. Sisson, H. Jiang, A. R. Francis, and M. M. Tanaka (2009) · 2009
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Model criticism based on likelihood-free inference, with an application to protein network evolution
Ratmann, O., C. Andrieu, T. Hinkley, C. Wiuf, and S. Richardson (2009) · 2009
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Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
Toni, T., D. Welch, N. Strelkowa, A. Ipsen, and M. P. H. Stumpf (2009) · 2009
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Estimating primate divergence times by using conditioned birth-and-death processes
Wilkinson, R. D. and S. Tavaré (2009) · 2009
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Approximate Bayesian computation in evolution and ecology
Beaumont, M. A. (2010) · 2010
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In defence of model-based inference in phylogeography
Beaumont, M. A., R. Nielsen, C. P. Robert, J. Hey, O. Gaggiotti, L. Knowles, A. Estoup, M. Panchal, J. Corander, M. Hickerson, S. A. Sisson, N. Fagundes, L. Chikhi, P. Beerli, R. Vitalis, J.-M. Corunet, J. Huelsenbeck, M. Foll, Z. Yang, F. Rousset, D. J. Balding, and L. Excoffier (2010) · 2010
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Abc as a flexible framework to estimate demography over space and time: Some cons, many pros
Bertorelle, G., A. Benazzo, and S. Mona (2010) · 2010
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Approximate Bayesian computation: a non-parametric perspective
Blum, M. G. B. (2010) · 2010
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Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation
Vo, B. N., C. C. Drovandi, A. N. Pettitt, and M. J. Simpson (2015) · 2015
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Historical environmental change in Africa drives divergence and admixture of aedes aegypti
Bennett, K. L., F. Shija, Y.-M. Linton, G. Misinzo, M. Kaddumukasa, R. Djouaka, O. Anyaele, A. Harris, S. Irish, T. Hliang, A. Prakash, J. Lutwama, and C. Walton (2016) · 2016
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Modelling extremes using approximate Bayesian computation
Erhardt, R. and S. A. Sisson (2016) · 2016
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Bayesian parameter estimation for the Wnt pathway: an infinite mixture models approach
Koutroumpas, K., P. Ballarini, I. Votsi, and P.-H. Cournede (2016) · 2016
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Inferring extrinsic noise from single-cell gene expression data using approximate Bayesian computation
Lenive, O., P. D. W. Kirk, and M. P. H. Stumpf (2016) · 2016
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Blum, M. G. B. and O. François (2010) · 2010
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HIV with contact-tracing: A case study in approximate Bayesian computation
Blum, M. G. B. and V. C. Tran (2010) · 2010
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Approximate Bayesian computation in practice
Csilléry, K., M. G. B. Blum, O. E. Gaggiotti, and O. François (2010) · 2010
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The ratio of human x chromosome to autosome diversity is positively correlated with genetic distance from genes
Hammer, M. F., A. E. Woerner, F. L. Mendez, J. C. Watkins, M. P. Cox, and J. D. Wall (2010) · 2010
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Bayesian symbol detection in wireless relay networks via likelihood-free inference
Peters, G. W., I. Nevat, S. A. Sisson, Y. Fan, and J. Yuan (2010) · 2010
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Statistical inference for noisy nonlinear ecological dynamic systems
Wood, S. N. (2010) · 2010
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Bayesian learning from marginal data in bionetwork models
Bonassi, F. V., L. You, and M. West (2011) · 2011
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Fundamentals and recent developments in approximate Bayesian computation
Lintusaari, J., M. U. Gutmann, R. Dutta, S. Kaski, and J. Corander (2016) · 2016
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Approximation of Bayesian predictive p p -values with regression ABC
Nott, D. J., C. C. Drovandi, K. Mengersen, and M. Evans (2016) · 2016
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Approximate Bayesian computation: A survey on recent results
Robert, C. P. (2016) · 2016
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Approximate Bayesian computation and model validation for repulsive spatial point processes
Shirota, S. and A. E. Gelfand (2016) · 2016
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Approximate Bayesian computation
Drovandi, C. C. (2017) · 2017
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Extending approximate Bayesian computation methods to high dimensions via Gaussian copula
Li, J., D. J. Nott, Y. Fan, and S. A. Sisson (2017) · 2017
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Adapting the abc distance function
Prangle, D. (2017) · 2017
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Bayesian synthetic likelihood
Price, L. F., C. C. Drovandi, A. Lee, and D. J. Nott (2017) · 2017
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Approximate Bayesian computation by subset simulation using hierarchical state space models
Vakilzadeh, M. K., Y. Huang, J. L. Beck, and T. Abrahamsson (2017) · 2017
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Theoretical and methodological aspects of MCMC computations with noisy likelihoods
Andrieu, C., A. Lee, and M. Vihola (2018) · 2018
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Divide and conquer in ABC: Expectation-Propagation algorithms for likelihood-free inference
Barthelmé, S., N. Chopin, and V. Cottet (2018) · 2018
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Regression approaches for ABC
Blum, M. G. B. (2018) · 2018
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ABC and indirect inference
Drovandi, C. C. (2018) · 2018
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Approximating the likelihood in approximate Bayesian computation
Drovandi, C. C., C. Grazian, K. Mengersen, and C. P. Robert (2018) · 2018
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Approximating the likelihood in Approximate Bayesian Computation
Drovandi, C. C., K. L. Mengersen, and C. P. Robert (2018) · 2018
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Application of approximate Bayesian computation to infer the genetic history of Pygmy hunter-gatherers populations from West Central Africa
Estoup, A., P. Verdu, J.-M. Marin, C. P. Robert, A. Dehne-Garcia, J.-M. Corunet, and P. Pudlo (2018) · 2018
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ABC in nuclear imaging
Fan, Y., S. R. Meikle, G. Angelis, and A. Sitek (2018) · 2018
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Abc samplers
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ABC in ecological modelling
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Asymptotics of abc
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ABC for climate: dealing with expensive simulators
Holden, P. B., N. R. Edwards, J. Hensman, and R. D. Wilkinson (2018) · 2018
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A guide to general purpose abc software
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ABC in systems biology
Liepe, J. and M. P. H. Stumpf (2018) · 2018
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Likelhood-free model choice
Marin, J.-M., P. Pudlo, A. Estoup, and C. P. Robert (2018) · 2018
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High-dimensional ABC
Nott, D. J., V. M.-H. Ong, Y. Fan, and S. A. Sisson (2018) · 2018
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SMC-ABC methods for estimation of stochastic simulation models of the limit order book
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Summary statistics in approximate Bayesian computation
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Informed choices: How to calibrate ABC with hypothesis testing
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Inferences on the acquisition of multidrug resistance in mycobacterium tuberculosis
Rodrigues, G. S., A. R. Francis, S. A. Sisson, and M. M. Tanaka (2018) · 2018
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On the history of ABC
Tavaré, S. (2018) · 2018
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Approximate Bayesian computation in population genetics
Beaumont, M. A., W. Zhang, and D. J. Balding (2002) · 2035
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