Hello list, I'm trying to carry out a global sensitivity analysis using the "sensitivity" package. I have a model with 26 paramters, mostly normally distributed (with a few truncated to not go below 0). I've been trying both the fast99 and sobol2007 functions, but having problems with both:
* with fast99, points seem to be generated at the minimum and maximum values a distribution can take, which is fine for qunif, but causes problems with qnorm, as it generates +-Inf values, which don't work with the model. * with sobol2007, I've done runs using 2x500 point samples, resulting in 14k runs. This gives quite wacky output, with both negative and very high values appearing in the first order and total indices (and associatedly large confidence intervals). As far as I can tell, my options are: * find a way to truncate the distributions for use with fast99 * increase the number of runs with sobol2007 Does anyone have any advice on which of these is more likely to work, or if there is an alternative route which would be better? Thanks! Dave Murray-Rust -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
