I am trying to understand what could be causing these strange values to appear on applying a Holt model to a vector. The data represents actual sales of an item.
library(forecast) sdata<-c(1955651,1691857,1617358,1509591,1452025,1387790,1630114,3522984,3322908,2315689, 4044634,11553435,9747305,5289976,3905946,1646080,1356731,1248135,1150756,848804,847815, 940673,1129751) > holt(sdata) Point Forecast Lo 80 Hi 80 Lo 95 Hi 95 24 6.144027e+122 6.144014e+122 6.144041e+122 6.144007e+122 6.144048e+122 25 6.144033e+122 4.502199e+122 7.785866e+122 3.633064e+122 8.655001e+122 26 6.144038e+122 3.822133e+122 8.465942e+122 2.592991e+122 9.695084e+122 27 6.144043e+122 3.300300e+122 8.987785e+122 1.794914e+122 1.049317e+123
This involves an exercise where a very large number of forecasts has to be generated. This is merely an attempt to find errors before the forecast is run across all the data. A number of records generated such strange records. I am sure there is a good explanation behind why we see such data.
Note that the data was coerced to a ts object prior to the model being applied on the same (and produced similar results)
Thanks in advance.