RAMAS Risk Calc

Risk Calc supports probability bounds analysis, standard fuzzy arithmetic, and classical interval analysis. Its applications are like those of Monte Carlo packages such as @Risk or Crystal Ball, but Risk Calc does not require you to specify precise details of statistical distributions and their dependency relationships when empirical data are lacking. Risk Calc makes new methods available for conducting distribution-free or nonparametric risk analyses. You decide what information or assumptions should be used, and the software calculates bounding estimates of risks. Often these bounds can be shown to be the best possible. Using Risk Calc, you can do quality assurance reviews for probabilistic risk and safety assessments


References in zbMATH (referenced in 17 articles )

Showing results 1 to 17 of 17.
Sorted by year (citations)

  1. Ferson, Scott; O’Rawe, Jason; Antonenko, Andrei; Siegrist, Jack; Mickley, James; Luhmann, Christian C.; Sentz, Kari; Finkel, Adam M.: Natural language of uncertainty: numeric hedge words (2015)
  2. Bouissou, Olivier; Goubault, Eric; Goubault-Larrecq, Jean; Putot, Sylvie: A generalization of $p$-boxes to affine arithmetic (2012)
  3. Kozine, Igor; Krymsky, Victor: An interval-valued reliability model with bounded failure rates (2012)
  4. Rebner, Gabor; Auer, Ekaterina; Luther, Wolfram: A verified realization of a Dempster-Shafer based fault tree analysis (2012)
  5. Elishakoff, Isaac; Ohsaki, Makoto: Optimization and anti-optimization of structures under uncertainty. (2010)
  6. Ben-Haim, Yakov; Dacso, Clifford C.; Carrasco, Jonathon; Rajan, Nithin: Heterogeneous uncertainties in cholesterol management (2009)
  7. Fuchs, Martin: Clouds, $p$-boxes, fuzzy sets, and other uncertainty representations in higher dimensions (2009)
  8. Fuchs, Martin; Neumaier, Arnold: Potential based clouds in robust design optimization (2009)
  9. Montgomery, Victoria J.; Coolen, Frank P.A.; Hart, Andy D.M.: Bayesian probability boxes in risk assessment (2009)
  10. Kreinovich, Vladik; Xiang, Gang: Fast algorithms for computing statistics under interval uncertainty: an overview (2008)
  11. Corliss, George; Foley, Christopher; Kearfott, R.Baker: Formulation for reliable analysis of structural frames (2007)
  12. Kreinovich, Vladik; Beck, Jan; Ferregut, Carlos; Sanchez, Araceli; Keller, G.Randy; Averill, Matthew; Starks, Scott A.: Monte-Carlo-type techniques for processing interval uncertainty, and their potential engineering applications (2007)
  13. Kreinovich, Vladik; Xiang, Gang; Starks, Scott A.; Longpré, Luc; Ceberio, Martine; Araiza, Roberto; Beck, Jan; Kandathi, Raj; Nayak, Asis; Torres, Roberto; Hajagos, Janos G.: Towards combining probabilistic and interval uncertainty in engineering calculations: algorithms for computing statistics under interval uncertainty, and their computational complexity (2006)
  14. Berleant, Daniel; Zhang, Jianzhong: Using Pearson correlation to improve envelopes around the distributions of functions (2004)
  15. Regan, Helen M.; Ferson, Scott; Berleant, Daniel: Equivalence of methods for uncertainty propagation of real-valued random variables (2004)
  16. Berleant, Daniel; Xie, Lizhi; Zhang, Jianzhong: Statool: A tool for distribution envelope determination (DEnv), an interval-based algorithm for arithmetic on random variables (2003)
  17. Kreinovich, Vladik; Ferson, Scott; Ginzburg, Lev: Exact upper bound on the mean of the product of many random variables with known expectations (2003)


Further publications can be found at: http://www.ramas.com/riskcalc.htm#refs