[R] Custom sampling method in R XXXX
Greg Snow
538280 at gmail.com
Mon Jun 23 23:26:17 CEST 2014
The sample function can be used to sample discrete values with
designated probabilities. I would just construct your list of 5
values based on the selected value (duplicating end values if needed,
so a choice of x=0 would be the vector c(0,0,0, 0.125, 0.25) ), then
sample from this vector with the probabilities that you specify.
On Mon, Jun 23, 2014 at 3:11 PM, Dan Abner <dan.abner99 at gmail.com> wrote:
> Hi all,
>
> I have the following situation and a good efficient way to perform
> this operation in R has not come to me. Any suggestions/input are
> welcome.
>
> I have a user-defined parameter (let's call it x) whose value is
> selected from a set of possible values (j). Once the user selects one
> of the values of j for x, then I need to map a probability
> distribution to the values of j such that the middle probability of
> .5385 (see probs below) is associated with the value of x and the tail
> probabilities are assigned to the 2 values below x and 2 values above
> x in j. Therefore, in the example below:
>
>
> x<-.250
> j<-c(0.000,0.125,0.250,0.375,0.500,0.625,0.750,0.875,1.000)
> probs<-c(0.02307692,0.20769231,0.53846154,0.20769231,0.02307692)
>
> probabilities would be assigned to the values of j as such:
>
> value probability
> 0 0.023077
> 0.125 0.207692
> 0.25 0.538462
> 0.375 0.207692
> 0.5 0.023077
>
> And then 1 value of j is selected based on the associated probability.
> Any ideas on an efficient way to do this?
>
> An added dimension of complexity is when the value of x is selected
> near the parameter boundary of j. If x = 0, then the easiest thing I
> can think of is to assign probabilities as:
>
> value probability
> 0 0.76923077
> 0.125 0.207692
> 0.25 0.023077
>
> However, I am open to other possibilities.
>
> Any assistance is appreciated.
>
> Thanks,
>
> Dan
>
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--
Gregory (Greg) L. Snow Ph.D.
538280 at gmail.com
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