메뉴 건너뛰기




Volumn 95, Issue 5, 2014, Pages 1418-1428

An approximate Bayesian computation approach to parameter estimation in a stochastic stage-structured population model

Author keywords

Approximate Bayesian computation; Cohort dynamics; Individual heterogeneity; Life history variation; Sequential Monte Carlo

Indexed keywords

BAYESIAN ANALYSIS; COHORT ANALYSIS; HETEROGENEITY; LIFE HISTORY TRAIT; MONTE CARLO ANALYSIS; POPULATION MODELING; POPULATION STRUCTURE; STOCHASTICITY;

EID: 84903555132     PISSN: 00129658     EISSN: None     Source Type: Journal    
DOI: 10.1890/13-1065.1     Document Type: Article
Times cited : (15)

References (43)
  • 1
    • 84860899405 scopus 로고    scopus 로고
    • Bayesian design strategies for synthetic biology
    • Barnes, C. P., D. Silk, and M. P. H. Stumpf. 2011. Bayesian design strategies for synthetic biology. Interface Focus 1:895- 908.
    • (2011) Interface Focus , vol.1 , pp. 895-908
    • Barnes, C.P.1    Silk, D.2    Stumpf, M.P.H.3
  • 2
    • 77955508453 scopus 로고    scopus 로고
    • Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model
    • Bazin, E., K. J. Dawson, and M. A. Beaumont. 2010. Likelihood-free inference of population structure and local adaptation in a Bayesian hierarchical model. Genetics 185: 587-602.
    • (2010) Genetics , vol.185 , pp. 587-602
    • Bazin, E.1    Dawson, K.J.2    Beaumont, M.A.3
  • 3
    • 78149388939 scopus 로고    scopus 로고
    • D. J. Futuyma, H. B. Shafer, and D. Simberloff, editors. Annual review of ecology, evolution, and systematics. 41. Annual Reviews, Palo Alto, California, USA
    • Beaumont, M. A. 2010. Approximate Bayesian computation in evolution and ecology. Pages 379-406 in D. J. Futuyma, H. B. Shafer, and D. Simberloff, editors. Annual review of ecology, evolution, and systematics. Volume 41. Annual Reviews, Palo Alto, California, USA.
    • (2010) Approximate Bayesian Computation in Evolution and Ecology , pp. 379-406
    • Beaumont, M.A.1
  • 5
    • 0036964474 scopus 로고    scopus 로고
    • Approximate Bayesian computation in population genetics
    • Beaumont, M. A., W. Zhang, and D. J. Balding. 2002. Approximate Bayesian computation in population genetics. Genetics 162:2025-2035.
    • (2002) Genetics , vol.162 , pp. 2025-2035
    • Beaumont, M.A.1    Zhang, W.2    Balding, D.J.3
  • 6
    • 33646879591 scopus 로고    scopus 로고
    • Population dynamics in a noisy world: Lessons from a mite experimental system
    • Academic Press, Waltham, Massachusetts, USA
    • Benton, T. G., A. P. Beckerman, and R. A. Desharnais. 2005. Population dynamics in a noisy world: lessons from a mite experimental system. Pages 143-181 in Population dynamics and laboratory ecology. Volume 37. Academic Press, Waltham, Massachusetts, USA.
    • (2005) Population Dynamics and Laboratory Ecology , vol.37 , pp. 143-181
    • Benton, T.G.1    Beckerman, A.P.2    Desharnais, R.A.3
  • 8
    • 73549122582 scopus 로고    scopus 로고
    • Nonlinear regression models for approximate Bayesian computation
    • Blum, M. G. B., and O. Franç ois. 2008. Nonlinear regression models for approximate Bayesian computation. Statistics and Computing 20:63-73.
    • (2008) Statistics and Computing , vol.20 , pp. 63-73
    • Blum, M.G.B.1    François, O.2
  • 9
    • 44649107771 scopus 로고    scopus 로고
    • An overview of existing methods and recent advances in sequential Monte Carlo
    • Cappé, O., S. Godsill, and E. Moulines. 2007. An overview of existing methods and recent advances in sequential Monte Carlo. Proceedings of the IEEE 95:899-924.
    • (2007) Proceedings of the IEEE , vol.95 , pp. 899-924
    • Cappé, O.1    Godsill, S.2    Moulines, E.3
  • 11
    • 56649113038 scopus 로고    scopus 로고
    • Inferring population history with DIY ABC: A user-friendly approach to approximate Bayesian computation
    • DOI 10.1093/bioinformatics/btn514
    • Cornuet, J.-M., F. Santos, M. A. Beaumont, C. P. Robert, J.-M. Marin, D. J. Balding, T. Guillemaud, and A. Estoup. 2008. Inferring population history with DIY ABC: a userfriendly approach to approximate Bayesian computation. Bioinformatics 24:2713-2719. (Pubitemid 352722613)
    • (2008) Bioinformatics , vol.24 , Issue.23 , pp. 2713-2719
    • Cornuet, J.-M.1    Santos, F.2    Beaumont, M.A.3    Robert, C.P.4    Marin, J.-M.5    Balding, D.J.6    Guillemaud, T.7    Estoup, A.8
  • 14
    • 70349939369 scopus 로고    scopus 로고
    • Stochastic development in biologically structured population models
    • de Valpine, P. 2009. Stochastic development in biologically structured population models. Ecology 90:2889-2901.
    • (2009) Ecology , vol.90 , pp. 2889-2901
    • De Valpine, P.1
  • 15
    • 79952603857 scopus 로고    scopus 로고
    • Estimation of parameters for macroparasite population evolution using approximate Bayesian computation
    • Drovandi, C. C., and A. N. Pettitt. 2011. Estimation of parameters for macroparasite population evolution using approximate Bayesian computation. Biometrics 67:225-233.
    • (2011) Biometrics , vol.67 , pp. 225-233
    • Drovandi, C.C.1    Pettitt, A.N.2
  • 18
    • 75249099118 scopus 로고    scopus 로고
    • ABC likelihood-free methods for model choice in Gibbs random fields
    • Grelaud, A., C. P. Robert, J. Marin, F. Rodolphe, and J. Taly. 2009. ABC likelihood-free methods for model choice in Gibbs random fields. Bayesian Analysis 4:317-335.
    • (2009) Bayesian Analysis , vol.4 , pp. 317-335
    • Grelaud, A.1    Robert, C.P.2    Marin, J.3    Rodolphe, F.4    Taly, J.5
  • 19
    • 20444406878 scopus 로고    scopus 로고
    • Bayesian estimation of recent migration rates after a spatial expansion
    • DOI 10.1534/genetics.104.034199
    • Hamilton, G., M. Currat, N. Ray, G. Heckel, M. Beaumont, and L. Excoffier. 2005. Bayesian estimation of recent migration rates after a spatial expansion. Genetics 170:409- 417. (Pubitemid 40800002)
    • (2005) Genetics , vol.170 , Issue.1 , pp. 409-417
    • Hamilton, G.1    Currat, M.2    Ray, N.3    Heckel, G.4    Beaumont, M.5    Excoffier, L.6
  • 20
    • 79960410421 scopus 로고    scopus 로고
    • Statistical inference for stochastic simulation models-theory and application
    • Hartig, F., J. M. Calabrese, B. Reineking, T. Wiegand, and A. Huth. 2011. Statistical inference for stochastic simulation models - theory and application. Ecology Letters 14:816- 827.
    • (2011) Ecology Letters , vol.14 , pp. 816-827
    • Hartig, F.1    Calabrese, J.M.2    Reineking, B.3    Wiegand, T.4    Huth, A.5
  • 23
    • 60649110912 scopus 로고    scopus 로고
    • Inferring the parameters of the neutral theory of biodiversity using phylogenetic information and implications for tropical forests
    • Jabot, F., and J. Chave. 2009. Inferring the parameters of the neutral theory of biodiversity using phylogenetic information and implications for tropical forests. Ecology Letters 12:239- 248.
    • (2009) Ecology Letters , vol.12 , pp. 239-248
    • Jabot, F.1    Chave, J.2
  • 24
    • 84879738527 scopus 로고    scopus 로고
    • EasyABC: Performing efficient approximate Bayesian computation sampling schemes using R
    • Jabot, F., T. Faure, and N. Dumoulin. 2013. EasyABC: performing efficient approximate Bayesian computation sampling schemes using R. Methods in Ecology and Evolution 4:684-687.
    • (2013) Methods in Ecology and Evolution , vol.4 , pp. 684-687
    • Jabot, F.1    Faure, T.2    Dumoulin, N.3
  • 25
    • 84862794744 scopus 로고    scopus 로고
    • Estimating demographic parameters from large-scale population genomic data using approximate Bayesian computation
    • Li, S., and M. Jakobsson. 2012. Estimating demographic parameters from large-scale population genomic data using approximate Bayesian computation. BMC Genetics 13:22.
    • (2012) BMC Genetics , vol.13 , pp. 22
    • Li, S.1    Jakobsson, M.2
  • 27
    • 77952098598 scopus 로고    scopus 로고
    • The use of approximate Bayesian computation in conservation genetics and its application in a case study on yellow-eyed penguins
    • Lopes, J. S., and S. Boessenkool. 2010. The use of approximate Bayesian computation in conservation genetics and its application in a case study on yellow-eyed penguins. Conservation Genetics 11:421-433.
    • (2010) Conservation Genetics , vol.11 , pp. 421-433
    • Lopes, J.S.1    Boessenkool, S.2
  • 30
    • 33751307421 scopus 로고    scopus 로고
    • Estimating recombination rates from single-nucleotide polymorphisms using summary statistics
    • DOI 10.1534/genetics.106.060723
    • Padhukasahasram, B., J. D. Wall, P. Marjoram, and M. Nordborg. 2006. Estimating recombination rates from singlenucleotide polymorphisms using summary statistics. Genetics 174:1517-1528. (Pubitemid 44808319)
    • (2006) Genetics , vol.174 , Issue.3 , pp. 1517-1528
    • Padhukasahasram, B.1    Wall, J.D.2    Marjoram, P.3    Nordborg, M.4
  • 32
    • 84863304598 scopus 로고    scopus 로고
    • R Development Core Team. R Foundation for Statistical Computing, Vienna, Austria.
    • R Development Core Team. 2010. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. www.r-project.org
    • (2010) R: A Language and Environment for Statistical Computing
  • 33
    • 72849152456 scopus 로고    scopus 로고
    • Heritability of extinction rates links diversification patterns in molecular phylogenies and fossils
    • Rabosky, D. L. 2009. Heritability of extinction rates links diversification patterns in molecular phylogenies and fossils. Systematic Biology 58:629-640.
    • (2009) Systematic Biology , vol.58 , pp. 629-640
    • Rabosky, D.L.1
  • 34
    • 84855501156 scopus 로고    scopus 로고
    • An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata
    • Rasmussen, R., and G. Hamilton. 2012. An approximate Bayesian computation approach for estimating parameters of complex environmental processes in a cellular automata. Environmental Modelling and Software 29:1-10.
    • (2012) Environmental Modelling and Software , vol.29 , pp. 1-10
    • Rasmussen, R.1    Hamilton, G.2
  • 35
  • 36
    • 0014257479 scopus 로고
    • A system of models for life cycle of a biological organism
    • Read, K., and J. R. Ashford. 1968. A system of models for life cycle of a biological organism. Biometrika 55:211-221.
    • (1968) Biometrika , vol.55 , pp. 211-221
    • Read, K.1    Ashford, J.R.2
  • 38
    • 33748541658 scopus 로고    scopus 로고
    • Evolution of intrahost HIV-1 genetic diversity during chronic infection
    • Shriner, D., Y. Liu, D. C. Nickle, and J. I. Mullins. 2006. Evolution of intrahost HIV-1 genetic diversity during chronic infection. Evolution 60:1165-1176.
    • (2006) Evolution , vol.60 , pp. 1165-1176
    • Shriner, D.1    Liu, Y.2    Nickle, D.C.3    Mullins, J.I.4
  • 39
    • 27544491192 scopus 로고    scopus 로고
    • ROCR: Visualizing classifier performance in R
    • DOI 10.1093/bioinformatics/bti623
    • Sing, T., O. Sander, N. Beerenwinkel, and T. Lengauer. 2005. ROCR: visualizing classifier performance in R. Bioinformatics 21:3940-3941. (Pubitemid 41535515)
    • (2005) Bioinformatics , vol.21 , Issue.20 , pp. 3940-3941
    • Sing, T.1    Sander, O.2    Beerenwinkel, N.3    Lengauer, T.4
  • 40
    • 0031014291 scopus 로고    scopus 로고
    • Inferring coalescence times from DNA sequence data
    • Tavare, S., D. J. Balding, R. C. Griffiths, and P. Donnelly. 1997. Inferring coalescence times from DNA sequence data. Genetics 145:505-518. (Pubitemid 27068401)
    • (1997) Genetics , vol.145 , Issue.2 , pp. 505-518
    • Tavare, S.1    Balding, D.J.2    Griffiths, R.C.3    Donnelly, P.4
  • 41
    • 58149142997 scopus 로고    scopus 로고
    • 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. Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society Interface 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.H.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.