I'm trying to forecast Poisson
data, divided in groups, of 1-26 months of data
, depending on the group. Of the pooled data 65% has a value of 0
and 25% a value of 1
. I couldn't find any trends or seasonality, so I started to test a couple of different stationairy models. MAMoving average (3)
, MAMoving Average (6)
, Simple Exponential Smoothing
, Naïve
and Simple Mean
.
I need to forecast 1-6 months ahead and used MAD
, MSE
and RMSE
to test the accuracy of the models. It looks like the most accurate is Simple Mean, with an RMSE of 1
and an MAD of 0,638
. I think this is really high but I have no clue how to do anything about this.
Are there forecasting methods I didn't think about that could be way better? Am I over-looking something?
The only thing I was able to find about prediction intervals was F+ts
and F-ts
with F
as forecast, t
as t distribution with alfa (n-2)
and s
as standard deviation. It don't think it was a really trustworthly source but since I wasn't able to find anything else, I'm not sure about how to set up those prediction intervals. Is this method right?
I don't have R to use. I need to do it myself.