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a week ago

Please I need suggestions on how to simulate count data from a Poisson distribution and fit (using PROC GLIMMIX) Normal, lognormal and negbin to the resulting data.Thank you

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## Re: Count Data

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Posted in reply to vdfdd

a week ago

Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and st...

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Posted in reply to Reeza

a week ago

Thank you for your swift response.

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Posted in reply to vdfdd

a week ago

Use the RAND('POISSON', mean) function in the DATA step to generate Poisson distributed data. Just set the desired value of the Poisson mean to produce a set of values. For example, these statements produce 100 observations in which Y has Poisson distributed values with mean=2.

```
data s;
do i=1 to 100;
y=rand("poisson",2);
output;
end;
run;
```

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Posted in reply to vdfdd

a week ago

Are you sure PROC GLIMMIX is the right tool for fitting this data?

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Posted in reply to draycut

a week ago

I am not completely sure. I was looking at the example in this link: https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_glimmix_sec...

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Posted in reply to vdfdd

a week ago

What are you trying to do overall? Why the need to simulate data?

@vdfdd wrote:

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Posted in reply to Reeza

a week ago

To test which distribution best fit the (non-normal, discrete) data

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Posted in reply to vdfdd

a week ago

PROC UNIVARIATE can test this with histogram statements.

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Posted in reply to Reeza

a week ago

Thank you for your suggestion.

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Posted in reply to vdfdd

a week ago

You could find answer at @Rick_SAS blog.