I have several forecasts and I am determined to combine them according to several weights.
Holt Winders = [rows = Calenderweeks, column =products]
Smoothing = [samething]c
and so on
As anyone suggestions on how I can manage that the best way?
Regarding that question: Can I combine columns simply by calling the columns iteratively of the different forecasting matrices?
In addition to the blog post that @EconomiCurtis shared, Hyndman also has an excellent book on forecasting that is freely available online and includes R code - it's one of the most practical and useful textbooks I've ever read. (The second edition is 2018 and the online version was last updated earlier this month). Here is his section on combining forecasts: https://otexts.org/fpp2/combinations.html
You may find the whole book useful though, depending on your project and timeline.
Update: To save everyone from needing to skim the link, the gist of the advice is that weighted averages don't seem to perform any better than unweighted
While there has been considerable research on using weighted averages, or some other more complicated combination approach, using a simple average has proven hard to beat.