Hi Heinz, Your code example is not working. The index ‘i’ runs out of bounds.
Regards, Rafael From: users [mailto:[email protected]] On Behalf Of Heinz Nabielek Sent: Monday, September 25, 2017 2:03 PM To: Users mailing list for Scilab <[email protected]> Subject: [Scilab-users] Is there a way to do it with Matrix Operations? Dear colleagues: in an attempt to code the generation of random deviates for a user-defined probability function p=[0.1176471 0.2352941 0.0588235 0.3882353 0.2 ], I spent only a few minutes to write the Scilab code below and it gives me all the solutions (frequency distribution of random numbers) that I need. N=100;X=grand(7,N,'def'); C=[];for j=1:7;Count(1:5)=0;for k=1:N;i=1;while X(j,k)>P(i);i=i+1;end;Count(i)=Count(i)+1;end;C=[C Count];end; and one typical sample run yields this C = 15. 9. 6. 12. 8. 12. 10. 20. 26. 38. 20. 23. 26. 24. 6. 7. 4. 7. 5. 10. 4. 38. 39. 32. 37. 48. 30. 39. 21. 19. 20. 24. 16. 22. 23. However, the for and while loops will be terribly inefficient and this is not good for large scale Monte-Carlo simulations. Is there a way to do it with Matrix Operations? Best greetings Heinz
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