THE TWO SHORT COMPUTER PROGRAMS PRESENTED IN THIS NOTE TAKLE THE PROBLEM OF ANALYSING MODEL OUTPUT UNCERTAINTY AND MODEL SENSITIVITIES. THE PREP PROGRAM (DATA PRE PROCESSING UNIT) PREPARES THE SAMPLE FOR A MONTECARLO SIMULATION USING THE DISTRIBUTION FUNCTIONS OF THE INPUT VARIABLES. THE USER IS ALLOWED TO SPECIFY ANY DEGREE OF CORRELATION AMONG THE VARIABLES. ONCE THE SAMPLE HAS BEEN GENERATED (WITH PREP) AND THE MONTECARLO SIMULATION HAS BEEN PERFORMED (WITH A USER SUPPLIED MODEL) THE UTILITY SPOP (STATISTICAL POST PROCESSING UNIT) COMES INTO USE, PERFORMING UNCERTAIN...
In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineer...
This package facilitates working with probability distributions by means of Monte-Carlo methods, in ...
The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides ...
A description and user's guide are given for a computer program, PATTRN, developed at Sandia Nationa...
Quantify uncertainty and sensitivities in your existing computational models with the “monaco” libra...
THE PAPER BRIEFLY REVIEWS THE EXISTING SAMPLING TECHNIQUES USED FOR MONTE CARLO SIMULATI...
Uncertainty analysis, based on Differential Sensitivity Analysis and Monte Carlo Analysis, has been ...
Many environmental and geographical models, such as those used in land degradation, agroecological a...
All features intended for the first version of Uncertainpy are completed, which includes quasi-Monte...
Computer models are crucial tools in engineering and environmental sciences for simulating the behav...
International audienceThe need for use of quantitative methods for characterizing variability and un...
By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (su...
All Monte Carlo computer codes have an uncertainty associated with the final result. This uncertaint...
An evaluation is made of the suitability of analytical and statistical sampling methods for making u...
Several hundred FDS simulations have been run using Monte Carlo analysis and probability distributio...
In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineer...
This package facilitates working with probability distributions by means of Monte-Carlo methods, in ...
The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides ...
A description and user's guide are given for a computer program, PATTRN, developed at Sandia Nationa...
Quantify uncertainty and sensitivities in your existing computational models with the “monaco” libra...
THE PAPER BRIEFLY REVIEWS THE EXISTING SAMPLING TECHNIQUES USED FOR MONTE CARLO SIMULATI...
Uncertainty analysis, based on Differential Sensitivity Analysis and Monte Carlo Analysis, has been ...
Many environmental and geographical models, such as those used in land degradation, agroecological a...
All features intended for the first version of Uncertainpy are completed, which includes quasi-Monte...
Computer models are crucial tools in engineering and environmental sciences for simulating the behav...
International audienceThe need for use of quantitative methods for characterizing variability and un...
By definition, computer simulation or Monte Carlo models are not solved by mathematical analysis (su...
All Monte Carlo computer codes have an uncertainty associated with the final result. This uncertaint...
An evaluation is made of the suitability of analytical and statistical sampling methods for making u...
Several hundred FDS simulations have been run using Monte Carlo analysis and probability distributio...
In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineer...
This package facilitates working with probability distributions by means of Monte-Carlo methods, in ...
The Guide to the Expression of Uncertainty in Measurement (usually referred to as the GUM) provides ...