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Poisson Random Number Generator

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Poisson Random Number Generator

Hello Everyone,

I am working on a Poisson Random Number Generator, and I had a question about it.

I know this may sound like a bit of a silly question, but I am wondering what does it output exactly?

Here is my code:

data test2;

  array p p1c1-p1c50;

  do i = 1 to 1000;

  do j=1 to 50 ;

  p=ranpoi(0,3);

  end;

  output;

  end;

  run;

proc print data=test2;

run;

So for my sanity, what this is outputting is the possible values that x can take with a lambda of 3.

Am I right in my thinking?

I just want to make sure because I had a bit of an embarrassing moment with my professor when he questioned me and asked me if I was sure about what this is outputting exactly.

Thanks!


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‎04-08-2013 08:28 PM
Respected Advisor
Posts: 4,920

Re: Poisson Random Number Generator

Posted in reply to InfoAlisaA

RanPoi(seed, m) returns pseudo random non-negative integers following a Poisson distribution with mean value = m. The Poisson distribution has the property that the variance is equal to the mean. The values that can be returned are thus 0, 1, 2, ...

PG

PG

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‎04-08-2013 08:28 PM
Respected Advisor
Posts: 4,920

Re: Poisson Random Number Generator

Posted in reply to InfoAlisaA

RanPoi(seed, m) returns pseudo random non-negative integers following a Poisson distribution with mean value = m. The Poisson distribution has the property that the variance is equal to the mean. The values that can be returned are thus 0, 1, 2, ...

PG

PG
Frequent Contributor
Posts: 90

Re: Poisson Random Number Generator

Thanks for your help! Smiley Happy I appreciate it!

SAS Super FREQ
Posts: 3,752

Re: Poisson Random Number Generator

Posted in reply to InfoAlisaA

And you can interpret it as the number of events that occur during a given time period if you know that the AVERAGE rate of the event is m events per time period (m does not need to be an integer). So, for example, if you receive an average of 6.3 emails per hour, and you start keeping count, you might observe 5 emails during the first hour, 8 during the next hour, 5 during the next hour, and so forth.   For a data-oriented tale of how the Poisson dstribution is used, see Fitting a Poisson distribution to data in SAS - The DO Loop

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