메뉴 건너뛰기




Volumn 56, Issue 2, 2012, Pages 69-85

A tutorial on approximate Bayesian computation

Author keywords

Approximate Bayesian computation; Bayesian estimation; Population Monte Carlo; Tutorial

Indexed keywords


EID: 84858767588     PISSN: 00222496     EISSN: 10960880     Source Type: Journal    
DOI: 10.1016/j.jmp.2012.02.005     Document Type: Article
Times cited : (224)

References (69)
  • 2
    • 80053457162 scopus 로고    scopus 로고
    • ABC-EP: expectation propagation for likelihood-free Bayesian computation
    • In Proceedings of the 28th international conference on machine learning. Bellevue, WA.
    • Barthelme, S., & Chopin, N. (2011). ABC-EP: expectation propagation for likelihood-free Bayesian computation. In Proceedings of the 28th international conference on machine learning. Bellevue, WA.
    • (2011)
    • Barthelme, S.1    Chopin, N.2
  • 3
    • 77955508453 scopus 로고    scopus 로고
    • Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model
    • Bazin E., Dawson K.J., Beaumont M.A. Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model. Genetics 2010, 185:587-602.
    • (2010) Genetics , vol.185 , pp. 587-602
    • Bazin, E.1    Dawson, K.J.2    Beaumont, M.A.3
  • 6
    • 0036964474 scopus 로고    scopus 로고
    • Approximate Bayesian computation in population genetics
    • Beaumont M.A., Zhang W., Balding D.J. Approximate Bayesian computation in population genetics. Genetics 2002, 162:2025-2035.
    • (2002) Genetics , vol.162 , pp. 2025-2035
    • Beaumont, M.A.1    Zhang, W.2    Balding, D.J.3
  • 7
    • 73549122582 scopus 로고    scopus 로고
    • Non-linear regression models for approximate Bayesian computation
    • Blum M.G.B., François O. Non-linear regression models for approximate Bayesian computation. Statistics and Computing 2010, 20:63-73.
    • (2010) Statistics and Computing , vol.20 , pp. 63-73
    • Blum, M.G.B.1    François, O.2
  • 9
  • 12
    • 33750047564 scopus 로고    scopus 로고
    • Differentiating the differentiation models: A comparison of the retrieving effectively from memory model (REM) and the subjective likelihood model (SLiM)
    • Criss A.H., McClelland J.L. Differentiating the differentiation models: A comparison of the retrieving effectively from memory model (REM) and the subjective likelihood model (SLiM). Journal of Memory and Language 2006, 55:447-460.
    • (2006) Journal of Memory and Language , vol.55 , pp. 447-460
    • Criss, A.H.1    McClelland, J.L.2
  • 14
    • 50849088636 scopus 로고    scopus 로고
    • Bayesian analysis of recognition memory: the case of the list-length effect
    • Dennis S., Lee M., Kinnell A. Bayesian analysis of recognition memory: the case of the list-length effect. Journal of Mathematical Psychology 2008, 59:361-376.
    • (2008) Journal of Mathematical Psychology , vol.59 , pp. 361-376
    • Dennis, S.1    Lee, M.2    Kinnell, A.3
  • 15
    • 49449113684 scopus 로고    scopus 로고
    • Convergence of adaptive mixtures of importance sampling schemes
    • Douc R., Guillin A., Marin J.-M., Robert C. Convergence of adaptive mixtures of importance sampling schemes. Annals of Statistics 2007, 35:420-448.
    • (2007) Annals of Statistics , vol.35 , pp. 420-448
    • Douc, R.1    Guillin, A.2    Marin, J.-M.3    Robert, C.4
  • 16
    • 0040601921 scopus 로고
    • Recognition memory and the operating characteristic
    • Tech. rep. AFCRC-TN-58-51. Hearing and Communication Laboratory. Indiana University. Bloomington, Indiana.
    • Egan, J. P. (1958). Recognition memory and the operating characteristic. Tech. rep. AFCRC-TN-58-51. Hearing and Communication Laboratory. Indiana University. Bloomington, Indiana.
    • (1958)
    • Egan, J.P.1
  • 17
    • 59049101673 scopus 로고    scopus 로고
    • Bayesian and maximum likelihood estimation of hierarchical response time models
    • Farrell S., Ludwig C.J.H. Bayesian and maximum likelihood estimation of hierarchical response time models. Psychonomic Bulletin and Review 2008, 15:1209-1217.
    • (2008) Psychonomic Bulletin and Review , vol.15 , pp. 1209-1217
    • Farrell, S.1    Ludwig, C.J.H.2
  • 22
    • 58149314233 scopus 로고    scopus 로고
    • Testing comparative phylogeographic models of marine vicariance and dispersal using a hierarchical Bayesian approach
    • Hickerson M.J., Meyer C. Testing comparative phylogeographic models of marine vicariance and dispersal using a hierarchical Bayesian approach. BMC Evolutionary Biology 2008, 8:322.
    • (2008) BMC Evolutionary Biology , vol.8 , pp. 322
    • Hickerson, M.J.1    Meyer, C.2
  • 23
    • 33846875227 scopus 로고    scopus 로고
    • Test for simultaneous divergence using approximate Bayesian computation
    • Hickerson M.J., Stahl E.A., Lessios H.A. Test for simultaneous divergence using approximate Bayesian computation. Evolution 2006, 60:2435-2453.
    • (2006) Evolution , vol.60 , pp. 2435-2453
    • Hickerson, M.J.1    Stahl, E.A.2    Lessios, H.A.3
  • 26
    • 10144233457 scopus 로고    scopus 로고
    • A Bayesian analysis of retention functions
    • Lee M.D. A Bayesian analysis of retention functions. Journal of Mathematical Psychology 2004, 48:310-321.
    • (2004) Journal of Mathematical Psychology , vol.48 , pp. 310-321
    • Lee, M.D.1
  • 27
    • 50849109367 scopus 로고    scopus 로고
    • Three case studies in the Bayesian analysis of cognitive models
    • Lee M.D. Three case studies in the Bayesian analysis of cognitive models. Psychonomic Bulletin and Review 2008, 15:1-15.
    • (2008) Psychonomic Bulletin and Review , vol.15 , pp. 1-15
    • Lee, M.D.1
  • 28
    • 84858783382 scopus 로고    scopus 로고
    • Special issue on hierarchical Bayesian models
    • Lee M.D. Special issue on hierarchical Bayesian models. Journal of Mathematical Psychology 2011, 55:1-118.
    • (2011) Journal of Mathematical Psychology , vol.55 , pp. 1-118
    • Lee, M.D.1
  • 29
    • 37349080640 scopus 로고    scopus 로고
    • A Bayesian approach to diffusion models of decision-making and response time
    • MIT Press, Cambridge, MA, B. Scholkopf, J. Platt, T. Hoffman (Eds.)
    • Lee M.D., Fuss I.G., Navarro D.J. A Bayesian approach to diffusion models of decision-making and response time. Advances in neural information processing 2006, 809-815. MIT Press, Cambridge, MA. 19th ed. B. Scholkopf, J. Platt, T. Hoffman (Eds.).
    • (2006) Advances in neural information processing , pp. 809-815
    • Lee, M.D.1    Fuss, I.G.2    Navarro, D.J.3
  • 30
    • 74249110200 scopus 로고    scopus 로고
    • Bayesian computation and model selection without likelihoods
    • Leuenberger C., Wegmann D. Bayesian computation and model selection without likelihoods. Genetics 2010, 184:243-252.
    • (2010) Genetics , vol.184 , pp. 243-252
    • Leuenberger, C.1    Wegmann, D.2
  • 31
    • 56549109467 scopus 로고    scopus 로고
    • Bayes factors: prior sensitivity and model generalizability
    • Liu C.C., Aitkin M. Bayes factors: prior sensitivity and model generalizability. Journal of Mathematical Psychology 2008, 52:362-375.
    • (2008) Journal of Mathematical Psychology , vol.52 , pp. 362-375
    • Liu, C.C.1    Aitkin, M.2
  • 34
    • 72449132133 scopus 로고    scopus 로고
    • Psychological interpretation of the ex-Gaussian and shifted wald parameters: a diffusion model analysis
    • Matzke D., Wagenmakers E.-J. Psychological interpretation of the ex-Gaussian and shifted wald parameters: a diffusion model analysis. Psychonomic Bulletin and Review 2009, 16:798-817.
    • (2009) Psychonomic Bulletin and Review , vol.16 , pp. 798-817
    • Matzke, D.1    Wagenmakers, E.-J.2
  • 35
    • 84858787392 scopus 로고    scopus 로고
    • REM integral expressions
    • Unpublished Manuscript.
    • Montenegro, M., Myung, J. I., & Pitt, M. A. (2011). REM integral expressions. Unpublished Manuscript.
    • (2011)
    • Montenegro, M.1    Myung, J.I.2    Pitt, M.A.3
  • 36
    • 0038172395 scopus 로고    scopus 로고
    • Tutorial on maximum likelihood estimation
    • Myung I.J. Tutorial on maximum likelihood estimation. Journal of Mathematical Psychology 2003, 47:90-100.
    • (2003) Journal of Mathematical Psychology , vol.47 , pp. 90-100
    • Myung, I.J.1
  • 39
    • 0022686961 scopus 로고
    • Attention, similarity, and the identification-categorization relationship
    • Nosofsky R.M. Attention, similarity, and the identification-categorization relationship. Journal of Experimental Psychology: General 1986, 115:39-57.
    • (1986) Journal of Experimental Psychology: General , vol.115 , pp. 39-57
    • Nosofsky, R.M.1
  • 40
    • 79954995450 scopus 로고    scopus 로고
    • Short-term memory scanning viewed as exemplar-based categorization
    • Nosofsky R.M., Little D.R., Donkin C., Fific M. Short-term memory scanning viewed as exemplar-based categorization. Psychological Review 2011, 118:280-315.
    • (2011) Psychological Review , vol.118 , pp. 280-315
    • Nosofsky, R.M.1    Little, D.R.2    Donkin, C.3    Fific, M.4
  • 41
    • 83755185629 scopus 로고    scopus 로고
    • A hierarchical latent stochastic differential equation model for affective dynamics
    • Oravecz Z., Tuerlinckx F., Vandekerckhove J. A hierarchical latent stochastic differential equation model for affective dynamics. Psychological Methods 2011, 16:468-490.
    • (2011) Psychological Methods , vol.16 , pp. 468-490
    • Oravecz, Z.1    Tuerlinckx, F.2    Vandekerckhove, J.3
  • 42
    • 0035380627 scopus 로고    scopus 로고
    • Generalization in interactive networks: the benefits of inhibitory competition and Hebbian learning
    • O'Reilly R.C. Generalization in interactive networks: the benefits of inhibitory competition and Hebbian learning. Neural Computation 2001, 13:1199-1242.
    • (2001) Neural Computation , vol.13 , pp. 1199-1242
    • O'Reilly, R.C.1
  • 43
    • 33749620330 scopus 로고    scopus 로고
    • Biologically based computational models of cortical cognition
    • O'Reilly R.C. Biologically based computational models of cortical cognition. Science 2006, 314:91-94.
    • (2006) Science , vol.314 , pp. 91-94
    • O'Reilly, R.C.1
  • 46
    • 27644559962 scopus 로고    scopus 로고
    • R Development Core Team
    • R: a language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. ISBN: 3-900051-07-0. URL: .
    • R Development Core Team (2008). R: a language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. ISBN: 3-900051-07-0. URL: http://www.R-project.org.
    • (2008)
  • 47
    • 58149404021 scopus 로고
    • A theory of memory retrieval
    • Ratcliff R. A theory of memory retrieval. Psychological Review 1978, 85:59-108.
    • (1978) Psychological Review , vol.85 , pp. 59-108
    • Ratcliff, R.1
  • 48
    • 0028470003 scopus 로고
    • Empirical generality of data from recognition memory receiver-operating characteristic functions and implications for the global memory models
    • Ratcliff R., McKoon G., Tindall M.H. Empirical generality of data from recognition memory receiver-operating characteristic functions and implications for the global memory models. Journal of Experimental Psychology: Learning, Memory, and Cognition 1994, 20:763-785.
    • (1994) Journal of Experimental Psychology: Learning, Memory, and Cognition , vol.20 , pp. 763-785
    • Ratcliff, R.1    McKoon, G.2    Tindall, M.H.3
  • 51
    • 31044444107 scopus 로고    scopus 로고
    • An introduction to Bayesian hierarchical models with an application in the theory of signal detection
    • Rouder J.N., Lu J. An introduction to Bayesian hierarchical models with an application in the theory of signal detection. Psychonomic Bulletin and Review 2005, 12:573-604.
    • (2005) Psychonomic Bulletin and Review , vol.12 , pp. 573-604
    • Rouder, J.N.1    Lu, J.2
  • 52
    • 4544303878 scopus 로고    scopus 로고
    • An evaluation of the vincentizing method of forming group-level response time distributions
    • Rouder J.N., Speckman P.L. An evaluation of the vincentizing method of forming group-level response time distributions. Psychonomic Bulletin and Review 2004, 11:419-427.
    • (2004) Psychonomic Bulletin and Review , vol.11 , pp. 419-427
    • Rouder, J.N.1    Speckman, P.L.2
  • 53
    • 0346706306 scopus 로고    scopus 로고
    • One hundred years of forgetting: a quantitative description of retention
    • Rubin D.C., Wenzel A.E. One hundred years of forgetting: a quantitative description of retention. Psychological Review 1996, 4:734-760.
    • (1996) Psychological Review , vol.4 , pp. 734-760
    • Rubin, D.C.1    Wenzel, A.E.2
  • 54
    • 57549108651 scopus 로고    scopus 로고
    • A survey of model evaluation approaches with a tutorial on hierarchical Bayesian methods
    • Shiffrin R.M., Lee M.D., Kim W., Wagenmakers E.-J. A survey of model evaluation approaches with a tutorial on hierarchical Bayesian methods. Cognitive Science 2008, 32:1248-1284.
    • (2008) Cognitive Science , vol.32 , pp. 1248-1284
    • Shiffrin, R.M.1    Lee, M.D.2    Kim, W.3    Wagenmakers, E.-J.4
  • 55
    • 0000803223 scopus 로고    scopus 로고
    • A model for recognition memory: REM-retrieving effectively from memory
    • Shiffrin R.M., Steyvers M. A model for recognition memory: REM-retrieving effectively from memory. Psychonomic Bulletin and Review 1997, 4:145-166.
    • (1997) Psychonomic Bulletin and Review , vol.4 , pp. 145-166
    • Shiffrin, R.M.1    Steyvers, M.2
  • 57
    • 67650327255 scopus 로고    scopus 로고
    • Approximate Bayeisian computation without summary statistics: the case of admixture
    • Sousa V.C., Fritz M., Beaumont M.A., Chikhi L. Approximate Bayeisian computation without summary statistics: the case of admixture. Genetics 2009, 181:1507-1519.
    • (2009) Genetics , vol.181 , pp. 1507-1519
    • Sousa, V.C.1    Fritz, M.2    Beaumont, M.A.3    Chikhi, L.4
  • 58
    • 58149142997 scopus 로고    scopus 로고
    • Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
    • Toni T., Welch D., Strelkowa N., Ipsen A., Stumpf M.P. Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society Interface 2009, 6:187-202.
    • (2009) Journal of the Royal Society Interface , vol.6 , pp. 187-202
    • Toni, T.1    Welch, D.2    Strelkowa, N.3    Ipsen, A.4    Stumpf, M.P.5
  • 59
    • 84858787398 scopus 로고    scopus 로고
    • Bayesian analysis of memory models
    • Manuscript in preparation.
    • Turner, B. M., Dennis, S., & Van Zandt, T. (2011). Bayesian analysis of memory models. Manuscript in preparation.
    • (2011)
    • Turner, B.M.1    Dennis, S.2    Van Zandt, T.3
  • 60
    • 84858755217 scopus 로고    scopus 로고
    • Approximate Bayesian computation with differential evolution
    • Manuscript (submitted for publication).
    • Turner, B. M., & Sederberg, P. B. (2012). Approximate Bayesian computation with differential evolution. Manuscript (submitted for publication).
    • (2012)
    • Turner, B.M.1    Sederberg, P.B.2
  • 61
    • 84897454625 scopus 로고    scopus 로고
    • Hierarchical approximate Bayesian computation
    • Manuscript (submitted for publication).
    • Turner, B. M., & Van Zandt, T. (2012). Hierarchical approximate Bayesian computation. Manuscript (submitted for publication).
    • (2012)
    • Turner, B.M.1    Van Zandt, T.2
  • 62
    • 85047685362 scopus 로고    scopus 로고
    • On the time course of perceptual choice: the leaky competing accumulator model
    • Usher M., McClelland J.L. On the time course of perceptual choice: the leaky competing accumulator model. Psychological Review 2001, 108:550-592.
    • (2001) Psychological Review , vol.108 , pp. 550-592
    • Usher, M.1    McClelland, J.L.2
  • 65
    • 70350136774 scopus 로고    scopus 로고
    • Efficient approximate Bayesian computation coupled with Markov chain Monte Carlo without likelihood
    • Wegmann D., Leuenberger C., Excoffier L. Efficient approximate Bayesian computation coupled with Markov chain Monte Carlo without likelihood. Genetics 2009, 182:1207-1218.
    • (2009) Genetics , vol.182 , pp. 1207-1218
    • Wegmann, D.1    Leuenberger, C.2    Excoffier, L.3
  • 67
    • 60749103064 scopus 로고    scopus 로고
    • Approximate Bayesian computation (ABC) gives exact results under the assumption of model error
    • Manuscript (submitted for publication).
    • Wilkinson, R. D. (2012). Approximate Bayesian computation (ABC) gives exact results under the assumption of model error. Manuscript (submitted for publication).
    • (2012)
    • Wilkinson, R.D.1
  • 69
    • 77956231279 scopus 로고    scopus 로고
    • Statistical inference for noisy nonlinear ecological dynamic systems
    • Wood S.N. Statistical inference for noisy nonlinear ecological dynamic systems. Nature 2010, 466:1102-1104.
    • (2010) Nature , vol.466 , pp. 1102-1104
    • Wood, S.N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.