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The belief index: An empirical measure for evaluating outcomes in Bayesian belief network modelling

Author

Listed:
  • Vilizzi, L.
  • Price, A.
  • Beesley, L.
  • Gawne, B.
  • King, A.J.
  • Koehn, J.D.
  • Meredith, S.N.
  • Nielsen, D.L.
  • Sharpe, C.P.

Abstract

Bayesian belief networks (BBNs) are a widespread tool for modelling the effects of management decisions and activities on a variety of environmental and ecological responses. Parameterisation of BBNs is often achieved by elicitation involving multiple experts, and this may result in different conditional probability distribution tables for the nodes in a BBN. Another common use of BBNs is in the comparison of alternative management scenarios. This paper describes and implements the ‘belief index’ (BI), an empirical measure for evaluating outcomes in BBN modelling that summarises the probabilities (or beliefs) of any one node in a BBN. A set of four species-specific BBNs for managing watering events for wetland fish is outlined and used to statistically assess between-expert and between-species variability in parameter estimates by means of the BI. Different scenarios for management decisions are also compared using the % improvement measure, a derivative of the BI.

Suggested Citation

  • Vilizzi, L. & Price, A. & Beesley, L. & Gawne, B. & King, A.J. & Koehn, J.D. & Meredith, S.N. & Nielsen, D.L. & Sharpe, C.P., 2012. "The belief index: An empirical measure for evaluating outcomes in Bayesian belief network modelling," Ecological Modelling, Elsevier, vol. 228(C), pages 123-129.
    • Handle: RePEc:eee:ecomod:v:228:y:2012:i:c:p:123-129
    DOI: 10.1016/j.ecolmodel.2012.01.005
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    References listed on IDEAS

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    1. Nicholson, Ann E. & Flores, M. Julia, 2011. "Combining state and transition models with dynamic Bayesian networks," Ecological Modelling, Elsevier, vol. 222(3), pages 555-566.
    2. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    3. Johnson, Sandra & Mengersen, Kerrie & de Waal, Alta & Marnewick, Kelly & Cilliers, Deon & Houser, Ann Marie & Boast, Lorraine, 2010. "Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle," Ecological Modelling, Elsevier, vol. 221(4), pages 641-651.
    4. Pollino, Carmel A. & White, Andrea K. & Hart, Barry T., 2007. "Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks," Ecological Modelling, Elsevier, vol. 201(1), pages 37-59.
    5. Renken, Henk & Mumby, Peter J., 2009. "Modelling the dynamics of coral reef macroalgae using a Bayesian belief network approach," Ecological Modelling, Elsevier, vol. 220(9), pages 1305-1314.
    6. Marti J. Anderson, 2006. "Distance-Based Tests for Homogeneity of Multivariate Dispersions," Biometrics, The International Biometric Society, vol. 62(1), pages 245-253, March.
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