The author has already gave the illustration and solution as well.

Thanks.



2013/6/9 Uwe Ligges <ligges@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
>>
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>>
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>>
>>

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