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Volumn 22, Issue 4, 2011, Pages 501-515

Estimating parameters for a stochastic dynamic marine ecological system

Author keywords

Data assimilation; Nonlinear dynamics; Numerical models; Parameter estimation; Particle filters; Sequential Monte Carlo; State augmentation; State space models; Stochastic differential equations

Indexed keywords

BIOGEOCHEMISTRY; DATA ASSIMILATION; GAUSSIAN METHOD; MARINE ECOSYSTEM; MONTE CARLO ANALYSIS; NUMERICAL MODEL; OBSERVATORY; PARAMETERIZATION; SENSITIVITY ANALYSIS; STOCHASTICITY;

EID: 79955634438     PISSN: 11804009     EISSN: 1099095X     Source Type: Journal    
DOI: 10.1002/env.1083     Document Type: Article
Times cited : (32)

References (52)
  • 2
    • 8744246331 scopus 로고    scopus 로고
    • Efficient parameter estimation for a highly chaotic system
    • Annan JD, Hargreaves JC. 2004. Efficient parameter estimation for a highly chaotic system. Tellus 56A: 520-526.
    • (2004) Tellus , vol.56 , pp. 520-526
    • Annan, J.D.1    Hargreaves, J.C.2
  • 4
    • 2942528794 scopus 로고    scopus 로고
    • Quantifying the effects of dynamical noise on the predictability of a simple ecosystem model
    • Bailey B, Doney SC, Lima ID. 2004. Quantifying the effects of dynamical noise on the predictability of a simple ecosystem model. Environmetrics 15: 337-355.
    • (2004) Environmetrics , vol.15 , pp. 337-355
    • Bailey, B.1    Doney, S.C.2    Lima, I.D.3
  • 6
    • 0035958646 scopus 로고    scopus 로고
    • Noisy clockwork: time series analysis of population fluctuations in animals
    • Bjørnstad ON, Grenfell BT. 2001. Noisy clockwork: time series analysis of population fluctuations in animals. Science 293: 638-643.
    • (2001) Science , vol.293 , pp. 638-643
    • Bjørnstad, O.N.1    Grenfell, B.T.2
  • 9
    • 6344233084 scopus 로고    scopus 로고
    • Dimensional reduction for a Bayesian filter. Proceedings of the National Academy of the Sciences 101(142).
    • Chorin AJ, Krause P. 2004. Dimensional reduction for a Bayesian filter. Proceedings of the National Academy of the Sciences 101(142): 15013-15017.
    • (2004) , pp. 15013-15017
    • Chorin, A.J.1    Krause, P.2
  • 11
    • 2942538599 scopus 로고    scopus 로고
    • Monte Carlo state space likelihoods by weighted posterior kernel density estimation
    • De Valpine P. 2004. Monte Carlo state space likelihoods by weighted posterior kernel density estimation. Journal of the American Statistical Association 99(466): 523-536.
    • (2004) Journal of the American Statistical Association , vol.99 , Issue.466 , pp. 523-536
    • De Valpine, P.1
  • 12
    • 0031518354 scopus 로고    scopus 로고
    • Long term variability of a stochastic forced pelagic ecosystem model
    • Dippner JW. 1997. Long term variability of a stochastic forced pelagic ecosystem model. Environmental Modeling and Assessment 2: 37-42
    • (1997) Environmental Modeling and Assessment , vol.2 , pp. 37-42
    • Dippner, J.W.1
  • 13
    • 0141803858 scopus 로고    scopus 로고
    • Parameter estimation in general state space models using particle methods
    • Doucet A, Tadić VB. 2003. Parameter estimation in general state space models using particle methods. Annals of the Institute of Statistical Mathematics 55(2): 409-422
    • (2003) Annals of the Institute of Statistical Mathematics , vol.55 , Issue.2 , pp. 409-422
    • Doucet, A.1    Tadić, V.B.2
  • 14
    • 13844320990 scopus 로고    scopus 로고
    • A biophysical coastal ecosystem model for assessing environmental effects of marine bivalve aquaculture
    • Dowd M. 2005. A biophysical coastal ecosystem model for assessing environmental effects of marine bivalve aquaculture. Ecological Modelling 183(2-3): 323-346.
    • (2005) Ecological Modelling , vol.183 , Issue.2-3 , pp. 323-346
    • Dowd, M.1
  • 15
    • 33745987359 scopus 로고    scopus 로고
    • A sequential Monte Carlo approach to marine ecological prediction
    • Dowd M. 2006. A sequential Monte Carlo approach to marine ecological prediction. Environmetrics 17: 435-455.
    • (2006) Environmetrics , vol.17 , pp. 435-455
    • Dowd, M.1
  • 16
    • 36048972344 scopus 로고    scopus 로고
    • Bayesian statistical data assimilation for ecosystem models using Markov chain Monte Carlo
    • Dowd M. 2007. Bayesian statistical data assimilation for ecosystem models using Markov chain Monte Carlo. Journal of Marine Systems 68: 439-456.
    • (2007) Journal of Marine Systems , vol.68 , pp. 439-456
    • Dowd, M.1
  • 17
    • 84884550570 scopus 로고    scopus 로고
    • The ensemble Kalman filter: theoretical formulation and practical implementation
    • Evensen G. 2003. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynamics 53: 343-367.
    • (2003) Ocean Dynamics , vol.53 , pp. 343-367
    • Evensen, G.1
  • 19
    • 33744996008 scopus 로고    scopus 로고
    • Ecosystem model complexity versus physical forcing: Quantification of their relative impact with assimilated Arabian Sea data
    • Friedrichs MAM, Hood RR, Wiggert JD. 2006. Ecosystem model complexity versus physical forcing: Quantification of their relative impact with assimilated Arabian Sea data. Deep Sea Research II 53: 576-600.
    • (2006) Deep Sea Research II , vol.53 , pp. 576-600
    • Friedrichs, M.A.M.1    Hood, R.R.2    Wiggert, J.D.3
  • 21
    • 0035648076 scopus 로고    scopus 로고
    • Following a moving target-Monte Carlo inference for dynamic Bayesian models
    • Gilks WR, Berzuini C. 2001. Following a moving target-Monte Carlo inference for dynamic Bayesian models. Journal of the Royal Statistical Society Series B 63(1): 127-146.
    • (2001) Journal of the Royal Statistical Society Series B , vol.63 , Issue.1 , pp. 127-146
    • Gilks, W.R.1    Berzuini, C.2
  • 23
    • 0027580559 scopus 로고
    • Novel approach to nonlinear/non-Gaussian Bayesian state estimation
    • Gordon NJ, Salmond DJ, Smith AFM. 1993. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings-F 140(2): 107-113.
    • (1993) IEE Proceedings-F , vol.140 , Issue.2 , pp. 107-113
    • Gordon, N.J.1    Salmond, D.J.2    Smith, A.F.M.3
  • 24
    • 0030838981 scopus 로고    scopus 로고
    • A Markov chain Monte Carlo method for estimation and assimilation into models
    • Harmon R, Challenor P. 1997. A Markov chain Monte Carlo method for estimation and assimilation into models. Ecological Modelling 101: 41-59.
    • (1997) Ecological Modelling , vol.101 , pp. 41-59
    • Harmon, R.1    Challenor, P.2
  • 26
    • 0004694060 scopus 로고    scopus 로고
    • Approximating and maximizing the likelihood for general state space models
    • Doucet A, de Freitas N, Gordon N (eds). Springer: New York.
    • Hürzeler M, Künsch HR. 2001. Approximating and maximizing the likelihood for general state space models. In Sequential Monte Carlo Methods in Practice, Doucet A, de Freitas N, Gordon N (eds). Springer: New York; 159-173.
    • (2001) Sequential Monte Carlo Methods in Practice , pp. 159-173
    • Hürzeler, M.1    Künsch, H.R.2
  • 30
    • 0030304310 scopus 로고    scopus 로고
    • Monte Carlo filter and smoother for non-Gaussian nonlinear state space models
    • Kitagawa G. 1996. Monte Carlo filter and smoother for non-Gaussian nonlinear state space models. Journal of Computational and Graphical Statistics 5: 1-25.
    • (1996) Journal of Computational and Graphical Statistics , vol.5 , pp. 1-25
    • Kitagawa, G.1
  • 32
    • 64149102810 scopus 로고    scopus 로고
    • Data assimilation for a coupled ocean atmosphere model. Part II: Parameter estimation
    • Kondrashov D, Sun C, Ghil M. 2008. Data assimilation for a coupled ocean atmosphere model. Part II: Parameter estimation. Monthly Weather Review 136(12): 5062-5076.
    • (2008) Monthly Weather Review , vol.136 , Issue.12 , pp. 5062-5076
    • Kondrashov, D.1    Sun, C.2    Ghil, M.3
  • 33
    • 30344486983 scopus 로고    scopus 로고
    • Recursive Monte Carlo filters: algorithms and theoretical analysis
    • Künsch HR. 2005. Recursive Monte Carlo filters: algorithms and theoretical analysis. The Annals of Statistics 33(5): 1983-2021.
    • (2005) The Annals of Statistics , vol.33 , Issue.5 , pp. 1983-2021
    • Künsch, H.R.1
  • 35
    • 34249822549 scopus 로고    scopus 로고
    • Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods
    • Lele SR, Dennis B, Lutscher F. 2007. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Ecology Letters 10: 551-563.
    • (2007) Ecology Letters , vol.10 , pp. 551-563
    • Lele, S.R.1    Dennis, B.2    Lutscher, F.3
  • 37
    • 0001225908 scopus 로고    scopus 로고
    • Combined parameter and state estimation in simulation based filtering
    • Doucet A, de Freitas N, Gordon N (eds). Springer: New York.
    • Liu J, West M. 2001. Combined parameter and state estimation in simulation based filtering. In Sequential Monte Carlo Methods in Practice, Doucet A, de Freitas N, Gordon N (eds). Springer: New York; 197-217.
    • (2001) Sequential Monte Carlo Methods in Practice , pp. 197-217
    • Liu, J.1    West, M.2
  • 39
    • 70350751436 scopus 로고    scopus 로고
    • Sequential data assimilation applied to a physical-biological model for the Bermuda Atlantic time series station
    • Mattern JP, Dowd M, Fennel, K. 2010. Sequential data assimilation applied to a physical-biological model for the Bermuda Atlantic time series station. Journal of Marine Systems 79: 144-156.
    • (2010) Journal of Marine Systems , vol.79 , pp. 144-156
    • Mattern, J.P.1    Dowd, M.2    Fennel, K.3
  • 40
    • 4444362798 scopus 로고    scopus 로고
    • Impacts of atmospheric variability on a coupled upper-ocean/ecosystem model of the subarctic Northeast Pacific
    • DOI:10.1029/2003GB002100
    • Monahan AH, Denman KL. 2004. Impacts of atmospheric variability on a coupled upper-ocean/ecosystem model of the subarctic Northeast Pacific. Global Biogeochemical Cycles 18, GB2010. DOI:10.1029/2003GB002100
    • (2004) Global Biogeochemical Cycles , vol.18
    • Monahan, A.H.1    Denman, K.L.2
  • 41
    • 0442293846 scopus 로고    scopus 로고
    • Inference for deterministic simulation models the Bayesian melding approach
    • Poole D, Raftery AE. 2000. Inference for deterministic simulation models the Bayesian melding approach. Journal of the American Statistical Association 95(452): 1244-1255.
    • (2000) Journal of the American Statistical Association , vol.95 , Issue.452 , pp. 1244-1255
    • Poole, D.1    Raftery, A.E.2
  • 46
    • 0035026330 scopus 로고    scopus 로고
    • Configuring an ecosystem model using data from the Bermuda-Atlantic time series (BATS)
    • Spitz YH, Moisan JR, Abbott MR. 2001. Configuring an ecosystem model using data from the Bermuda-Atlantic time series (BATS). Deep-Sea Research II 48: 1733-1768.
    • (2001) Deep-Sea Research II , vol.48 , pp. 1733-1768
    • Spitz, Y.H.1    Moisan, J.R.2    Abbott, M.R.3
  • 47
    • 0035402237 scopus 로고    scopus 로고
    • Estimation of unknown parameters in nonlinear and non-Gaussian state space models
    • Tanizaki H. 2001. Estimation of unknown parameters in nonlinear and non-Gaussian state space models. Journal of Statistical Planning and Inference 96(2): 301-323.
    • (2001) Journal of Statistical Planning and Inference , vol.96 , Issue.2 , pp. 301-323
    • Tanizaki, H.1
  • 48
    • 0034105166 scopus 로고    scopus 로고
    • Oceanographic data assimilation and regression analysis
    • Thompson KR, Dowd M, Lu Y, Smith B. 2000. Oceanographic data assimilation and regression analysis. Environmetrics 11: 183-196.
    • (2000) Environmetrics , vol.11 , pp. 183-196
    • Thompson, K.R.1    Dowd, M.2    Lu, Y.3    Smith, B.4
  • 49
    • 0034091301 scopus 로고    scopus 로고
    • Improving marine ecosystem models: use of data assimilation and mesocosm experiments
    • Vallino JJ. 2000. Improving marine ecosystem models: use of data assimilation and mesocosm experiments. Journal of Marine Research 58: 117-164.
    • (2000) Journal of Marine Research , vol.58 , pp. 117-164
    • Vallino, J.J.1
  • 50
    • 19444379764 scopus 로고    scopus 로고
    • CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm: experimental results and comparison with the DFO algorithm
    • Vanden Berghen F, Hugues Bersini H. 2005. CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm: experimental results and comparison with the DFO algorithm. Journal of Computational and Applied Mathematics 181(1): 157-175.
    • (2005) Journal of Computational and Applied Mathematics , vol.181 , Issue.1 , pp. 157-175
    • Vanden Berghen, F.1    Hugues, B.H.2
  • 51
    • 0142010030 scopus 로고    scopus 로고
    • A variance-minimizing filter for large-scale applications
    • Van Leeuwen PJ. 2003. A variance-minimizing filter for large-scale applications. Monthly Weather Review 131: 2071-2084.
    • (2003) Monthly Weather Review , vol.131 , pp. 2071-2084
    • Van Leeuwen, P.J.1
  • 52
    • 0041985115 scopus 로고    scopus 로고
    • Hierarchical Bayesian models for predicting the spread of ecological processes
    • Wikle CW. 2003. Hierarchical Bayesian models for predicting the spread of ecological processes. Ecology 84(6): 1382-1394.
    • (2003) Ecology , vol.84 , Issue.6 , pp. 1382-1394
    • Wikle, C.W.1


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