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I have been trying to do the forecasting model.

There is biological data (pollen grain in the air, which appears each year during the spring/summer time).

My data has daily value and there is an annual seasonality.

My question is which model will be the best?

I have tried with 1) auto.arima: Series: traning ARIMA(5,1,0)

2) TBATS: TBATS(1, {2,1}, 0.894, {<365.25,13>}) 3) stlf 4) arima with Fourier terms

5) croston

But I think these all are not good in this case. There is a too long period and too many zeros.

I would like to create a forecasting model using this historical data and do short term forecasts for the future. 2-, 3- days ahead.

I would be really grateful for any suggestions and hints.

My data looks like: enter image description here

enter image description here

enter image description here

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    $\begingroup$ Why don't you post your actual data ? $\endgroup$ – IrishStat Dec 18 '19 at 12:26
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I have a pretty big time series - daily time series of pollen observation gathered for 30 years. I tried to put my data and also improve a bit my question but I can not see any of my changes. I do not know why.

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