Active Filters

  • (-) Keywords = imprecise probabilities
Search Results 1 - 6 of 6
  • RSS Feed
Select Page
Towards a comprehensive uncertainty assessment in environmental research and decision support
Reichert, P. (2020). Towards a comprehensive uncertainty assessment in environmental research and decision support. Water Science and Technology, 81(8), 1588-1596. https://doi.org/10.2166/wst.2020.032
The effect of ambiguous prior knowledge on Bayesian model parameter inference and prediction
Rinderknecht, S. L., Albert, C., Borsuk, M. E., Schuwirth, N., K√ľnsch, H. R., & Reichert, P. (2014). The effect of ambiguous prior knowledge on Bayesian model parameter inference and prediction. Environmental Modelling and Software, 62, 300-315. https://doi.org/10.1016/j.envsoft.2014.08.020
Conceptual and practical aspects of quantifying uncertainty in environmental modelling and decision support
Reichert, P. (2012). Conceptual and practical aspects of quantifying uncertainty in environmental modelling and decision support. In R. Seppelt, A. A. Voinov, S. Lange, & D. Bankamp (Eds.), Proceedings of the 6th biennial meeting of the international environmental modelling and software society. Managing resources of a limited planet (pp. 1013-1020). International Environmental Modelling and Software Society.
Bridging uncertain and ambiguous knowledge with imprecise probabilities
Rinderknecht, S. L., Borsuk, M. E., & Reichert, P. (2012). Bridging uncertain and ambiguous knowledge with imprecise probabilities. Environmental Modelling and Software, 36, 122-130. https://doi.org/10.1016/j.envsoft.2011.07.022
Eliciting Density Ratio Classes
Rinderknecht, S. L., Borsuk, M. E., & Reichert, P. (2011). Eliciting Density Ratio Classes. International Journal of Approximate Reasoning, 52(6), 792-804. https://doi.org/10.1016/j.ijar.2011.02.002
On the necessity of using imprecise probabilities for modelling environmental systems
Reichert, P. (1997). On the necessity of using imprecise probabilities for modelling environmental systems. Water Science and Technology, 36(5), 149-156. https://doi.org/10.1016/S0273-1223(97)00469-1