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From |
"Michael Blasnik" <michael.blasnik@verizon.net> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: general simulation program (postfile) |

Date |
Fri, 15 Aug 2003 12:41:53 -0400 |

I have a couple of suggestions to improve or speed up your program. 1) You could generate 1000 poisson random numbers at a time at the beginning of the program (instead of just one at a time) and then use a loop to move n1 n2 and n into local macros (e.g., n1_`i', n2_`i', n_`i'). Then you could run the main loop referencing these locals. This might make your code look a little better and run a little faster. I would also look into just grabbing the algorithms from within rndpoi and integrating that into your loop. 2) You could replace -nearest- with an alternative that I've written that's about 10x faster. -nearest- uses brute force to compare each observation to every other observation in the dataset one at a time (execution time growing with n^2). The approach I used only loops through the obervations once, calculating a tempvar for distance and sorting the dataset to find the nearest match. The execution speed improvement from this approach can be an order of magnitude. I tried your program and then ran it again using this -nearest- replacement and found that, with lambda1=20 and lambda2=30, execution time goes from 230 seconds to 30 seconds. I then tried a version incorporating my first suggestion and execution time dropped to 18 seconds. The speed improvement from the -nearest- replacement would be even larger with larger values of lambda (I got tired of waiting with values of 40 and 80) If you want a copy of nearest2, email me directly and I can send it to you. Michael Blasnik michael.blasnik@verizon.net ----- Original Message ----- From: "Benoit Dulong" <bendulong@vdn.ca> To: "statalist" <statalist@hsphsun2.harvard.edu> Sent: Friday, August 15, 2003 10:40 AM Subject: st: general simulation program (postfile) > The following simulation program will be the first Stata program > presented to my director at University of Montreal. > It works, but it is slow, and it feels bizarre... > (I have to drop _all two times) > > Question-1 > In general, is that how a simulation should be done with Stata > (postfile, post, postclose) ? > > Question-2 > To generate a random number n1, I use two syntax lines: > -------------------- > rndpoi 1 `lambda1' > local n1 = xp > -------------------- > Is it possible to do this in only one syntax line ? > (pass directly the random number to local n1) > > Question-3 > It it possible not to drop _all two times ? > (use subroutine ?) > > Thank you. > Benoit Dulong > > ---------------------------------------------------------------------- > MY ALGORITHM > ---------------------------------------------------------------------- > > [1] > generate random number n1 > from a Poisson distribution with parameter lambda1 > > generate random number n2 > from a Poisson distribution with parameter lambda2 > > n = n1+n1 > > [2] > generate random vector x (n component) > from uniform distribution (generate x=uniform()) > > generate random vector y (n component) > from uniform distribution (generate y=uniform()) > > [3] > for each (x[i],y[i]), i=1...n, > calculate the distance to the nearest neighbor > using -- nearest -- from N.J COX (NJC 1.1.0 10 January 2003) > the syntax > nearest x y, id(id) dist(h) > gives a file with n rows and 4 columns (x y id h) > > [4] > from the file obtained in [3] > calculate the mean (mh) and var (vh) of the n values of h > > [5] > repeat [1] to [4] 1000 times > > ---------------------------------------------------------------------- > MY PROGRAM > ---------------------------------------------------------------------- > > program define myprog1 > version 7.0 > args lambda1 lambda2 > > postfile mysim1 n1 n2 n mh vh using "myresults1", replace > > forvalues i=1(1)1000{ > > drop _all > > display "i= " `i' > > rndpoi 1 `lambda1' > local n1 = xp > > rndpoi 1 `lambda2' > local n2 = xp > > local n = `n1' + `n2' > > drop _all > set obs `n' > > gen x = uniform() > gen y = uniform() > nearest x y, id(id) dist(h) > > summarize h > local mh = r(mean) > local vh = r(Var) > > post mysim1 (`n1') (`n2') (`n') (`mh') (`vh') > > } > > postclose mysim1 > > end > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: general simulation program (postfile)***From:*Benoit Dulong <bendulong@vdn.ca>

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