It seams that fast99 function (sensitivity package) does not work out for norm distribution.

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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