Blar i Centre for the Study of the Sciences and the Humanities (SVT) på tidsskrift "Environmental Modelling & Software"

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    • The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support 

      Razavi, Saman; Jakeman, Anthony; Saltelli, Andrea; Prieur, Clémentine; Iooss, Bertrand; Borgonovo, Emanuele; Plischke, Elmar; Lo Piano, Samuele; Iwanaga, Takuya; Becker, William; Tarantola, Stefano; Guillaume, Joseph H.A.; Jakeman, John; Gupta, Hoshin; Melillo, Nicola; Rabitti, Giovanni; Chabridon, Vincent; Duan, Qingyun; Sun, Xifu; Smith, Stefán; Sheikholeslami, Razi; Hosseini, Nasim; Asadzadeh, Masoud; Puy, Arnald; Kucherenko, Sergei; Maier, Holger R. (Journal article; Peer reviewed, 2021)
      Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven ...

    • Is VARS more intuitive and efficient than Sobol’ indices? 

      Maeso, Arnald Puy; Lo Piano, Samuele; Saltelli, Andrea (Journal article; Peer reviewed, 2021)
      The Variogram Analysis of Response Surfaces (VARS) has been proposed by Razavi and Gupta as a new comprehensive framework in sensitivity analysis. According to these authors, VARS provides a more intuitive notion of ...

    • Sensitivity analysis: A discipline coming of age 

      Saltelli, Andrea; Jakeman, Anthony; Razavi, Saman; Wu, Qiongli (Journal article; Peer reviewed, 2021)
      Sensitivity analysis (SA) as a ‘formal’ and ‘standard’ component of scientific development and policy support is relatively young. Many researchers and practitioners from a wide range of disciplines have contributed to SA ...

    • Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices 

      Saltelli, Andrea; Aleksankina, Ksenia; Becker, William; Fennell, Pamela; Ferretti, Frederico; Holst, Niels; Li, Sushan; Wu, Qiongli (Journal article; Peer reviewed, 2019-04)
      Sensitivity analysis provides information on the relative importance of model input parameters and assumptions. It is distinct from uncertainty analysis, which addresses the question ‘How uncertain is the prediction?’ ...