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Volumn 26, Issue 9, 2007, Pages 1867-1872

Bayesian multimodel inference for dose-response studies

Author keywords

Bayesian inference; Dose response; Methylmercury; Model selection; Multimodel inference

Indexed keywords

MATHEMATICAL MODELS; NUTRITION; ORGANOMETALLICS; PARAMETER ESTIMATION; STATISTICAL METHODS; UNCERTAIN SYSTEMS;

EID: 34548484609     PISSN: 07307268     EISSN: None     Source Type: Journal    
DOI: 10.1897/06-597R.1     Document Type: Article
Times cited : (8)

References (16)
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  • 3
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    • The use of Bayesian model averaging to better represent uncertainty in ecological models
    • Wintle BA, McCarthy MA, Volinsky CT, Kavanagh RP. 2003. The use of Bayesian model averaging to better represent uncertainty in ecological models. Conserv Biol 17:1579-1590.
    • (2003) Conserv Biol , vol.17 , pp. 1579-1590
    • Wintle, B.A.1    McCarthy, M.A.2    Volinsky, C.T.3    Kavanagh, R.P.4
  • 4
  • 6
    • 0036527211 scopus 로고    scopus 로고
    • Of BUGS and birds: Markov chain Monte Carlo for hierarchical modeling in wildlife research
    • Link WA, Cam E, Nichols JD, Cooch EG. 2002. Of BUGS and birds: Markov chain Monte Carlo for hierarchical modeling in wildlife research. J Wild Manag 66:277-291.
    • (2002) J Wild Manag , vol.66 , pp. 277-291
    • Link, W.A.1    Cam, E.2    Nichols, J.D.3    Cooch, E.G.4
  • 8
    • 0002276308 scopus 로고
    • Assessment and propagation of model uncertainty (with discussion)
    • Draper D. 1995. Assessment and propagation of model uncertainty (with discussion). Journal of the Royal Statistical Society B 57:45-97.
    • (1995) Journal of the Royal Statistical Society B , vol.57 , pp. 45-97
    • Draper, D.1
  • 10
    • 33845360384 scopus 로고    scopus 로고
    • Model weights and the foundations of multimodel inference
    • Link WA, Barker RJ. 2006. Model weights and the foundations of multimodel inference. Ecology 87:2626-2635.
    • (2006) Ecology , vol.87 , pp. 2626-2635
    • Link, W.A.1    Barker, R.J.2
  • 14
    • 0002471741 scopus 로고    scopus 로고
    • Discussion: Should ecologists become Bayesians?
    • Dennis B. 1996. Discussion: Should ecologists become Bayesians? Ecol Appl 6:1095-1103.
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    • Dennis, B.1
  • 15
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    • Understanding the Metropolis-Hastings algorithm
    • Chib S, Greenberg E. 1995. Understanding the Metropolis-Hastings algorithm. American Statistician 49:327-335.
    • (1995) American Statistician , vol.49 , pp. 327-335
    • Chib, S.1    Greenberg, E.2
  • 16
    • 34548483567 scopus 로고    scopus 로고
    • Spiegelhalter DJ, Thomas A, Best NG, Gilks WR. 1995. BUGS: Bayesian Inference Using Gibbs Sampling, Ver 0.5. University of Cambridges, Biostatistics Unit, Cambridge, UK
    • Spiegelhalter DJ, Thomas A, Best NG, Gilks WR. 1995. BUGS: Bayesian Inference Using Gibbs Sampling, Ver 0.5. University of Cambridges, Biostatistics Unit, Cambridge, UK.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.