I know this question is kind of complicated to understand at first. Here's the deal:
I've got organized, monthly sales data from various years, and when I graphed it I saw there's (obviously) a general behavior throughout the year (not taking into account the effect of external or internal factors which could affect the general behavior of the data). I would like to know if there is a method with which I could express the expected value of the data during that month, based on the historical data, for forecasting purposes.
It would be like some kind of regression, but in this case my data is not distributed parametrically, so Excel's trendlines and regular regressions can't help me. Maybe a non-parametric regression? I don't know any nor its logic behind, so if you know, please help me with it.
EDIT: Here I show you a graph of the time series per year, as well as a yearly weighted average of how the data behaves monthly (the weights were the % that each year represented vs the total of all years). I wouldn't want a parametric function that can't adjust properly to the data because each peak is a characteristic behavior of the time series during that month. Also, the autocorrelation function is below the Data graphs (from k = 1 to 83, as I have 7 years (= 84 months) of data. I think that much should be enough.