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improving speed of simulation using random numbers

  • To: mathgroup at smc.vnet.net
  • Subject: [mg128662] improving speed of simulation using random numbers
  • From: felipe.benguria at gmail.com
  • Date: Thu, 15 Nov 2012 03:56:34 -0500 (EST)
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  • Delivered-to: l-mathgroup@wolfram.com
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Dear all, 

I am trying to compute an expected value using simulation.
I have a random number x with density function d[x]. I want to compute the expected value of function f[x], which is equal to the integral of f[x] times 
d[x] over x.  
In my case, it is difficult to compute the integral so I simulate N values for x and compute the average of f[x] over all N simulated values.

My problem is that my code takes to long for my purposes: this is a part of a larger program and is making it unfeasible in terms of time. 

The following code provides an example of the situation, and my question is how could I reduce the time this takes. THanks a lot for your help

g[x_]:= x^2

 
mydensity[myparameter_]:= ProbabilityDistribution[myparameter*(t)^(-myparameter - 1), {t, 1, Infinity}]

randomnum[myparameter_] := RandomVariate[draw[myparameter], 50]

 
Timing[Sum[g[randomnum[5][[i]]], {i, 1, 50}]]

Out[1353]= {0.64, 81.7808}

This takes 0.6 seconds in my computer and that is way too long for my full program ( I do this many times).

Thanks again,
Felipe



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