It is the problem of norm distribution. You know that 0 and 1are
coresponding to -inf and inf by qnorm function, which is no physical
meaning. That is why NA occured in sensitivity index. The author
recommended either using truncated norm distribution or tricky number of
sampling to avoid the 0 and 1.
2013/6/10 David Winsemius <dwinsem...@comcast.net>
>
> On Jun 9, 2013, at 4:08 PM, Marino David wrote:
>
> > The author has already gave the illustration and solution as well.
> >
>
> Is that supposed to mean that you emailed the author and got a private
> response?
>
> > Thanks.
> >
> >
> >
> > 2013/6/9 Uwe Ligges <lig...@statistik.tu-dortmund.de>
> >
> >>
> >>
> >> On 08.06.2013 00:54, Marino David wrote:
> >>
> >>> 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?
> >>>
> >>
> >> Why not ask the authors of the function?
> >>
> >> Best,
> >> Uwe Ligges
> >>
> >>
> >>> 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
> >>>
> >>> [[alternative HTML version deleted]]
>
> --
>
> David Winsemius
> Alameda, CA, USA
>
>
[[alternative HTML version deleted]]
______________________________________________
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.
