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FreelanceReinh · ‎01-15-2020

@BillT wrote: to calculate the cumulative probabilities, I added a line before the 'output' statement of the skellam datastep: 'cp+p;' This should be fine. If in doubt, just increase the value of macro variable c. As soon as the largest computed cp values are equal to 1 (within the accuracy limits), you see that the omitted lower tail of the distribution (i.e., the sum of the p values for x<floor(m-&c*s)) was negligible.

PaigeMiller · ‎10-30-2019

@BillT wrote: We have not been able to get SAS to produce prediction limits. Why not? What happens? Show us the code. Show us the LOG. Show us a portion of the data. I also would like to know how SAS produces the predictions and their confidence limits. Predictions are created using the fitted model equation. The confidence interval formulas are shown at the link you gave. The SAS documentation indicates the leverage and weights are used to produce the limits however, the scored data do not include weights or leverage values. If you don't have weights, then every observation gets a weight of 1. Every observation has a leverage, it is computed from the data.

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Re: SAS function for the skellam distribution

Re: SAS function for the skellam distribution

SAS function for the skellam distribution

Proc NLIN prediction limits for scored data (i.e., records with missin...

SAS function for the skellam distribution

Re: SAS function for the skellam distribution

Re: Proc NLIN prediction limits for scored data (i.e., records with mi...