Dear all mailing listers,
Does Anyone have the same problem as mine when using the fast99
(extended-FAST method) to perform SA of model with norm distribution inputs?
See the simple example given following.
Any suggestion will be greatly appreciated.
Thank you!
Marino
# Simple example
# 1. uniform version (It works well)
library(sensitivity)
Myfun<-function(x){return(rowSums(x))}
SA1 <- fast99(model = Myfun, factors = 3, n = 1000, q = "qunif", q.arg =
list(min = 0, max = 1))
> SA1
Call:
fast99(model = Myfun, factors = 3, n = 1000, q = "qunif", q.arg =
list(min = 0, max = 1))
Model runs: 3000
Estimations of the indices:
first order total order
X1 0.3335243 0.3350584
X2 0.3335243 0.3350584
X3 0.3335243 0.3350584
# 2. norm version (it does not work)
SA2 <- fast99(model = Myfun, factors = 3, n = 1000, q = "qnorm", q.arg =
list(mean = 0, sd = 1))
> SA2
Call:
fast99(model = Myfun, factors = 3, n = 1000, q = "qnorm", q.arg =
list(mean = 0, sd = 1))
Model runs: 3000
Estimations of the indices:
first order total order
X1 NA NA
X2 NA NA
X3 NA NA
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