Hi all,Lets say after waiting for a few days, I've gotten a 8-dimensional Sharpe Ratio array...What's the best way to "visualize" or make sense out of the 8-D array?Are there tools in R that allow us to "explore" this multi-dimensional array?I am thinking of the following "flattened" structure, and hopefully writing to CSV file and opening in Excel will help a bit?But I am not totally sure... and I am really newbie on this...The flattened structure can be described in the following forms:count=0for (i1 in Parameter1Set)for (i2 in Parameter2Set)for (i3 in Parameter3Set)for (i4 in Parameter4Set)for (i5 in Parameter5Set)for (i6 in Parameter6Set)for (i7 in Parameter7Set)for (i8 in Parameter8Set){ count=count+1 results[count, 1]=i1 results[count, 2]=i2 results[count, 3]=i3 results[count, 4]=i4 results[count, 5]=i5 results[count, 6]=i6 results[count, 7]=i7 results[count, 8]=i8 mySharpeRatio=RunBacktest(i1, i2, i3, i4, i5, i6, i7, i8) results[count, 9]=mySharpeRatio}Any suggestions/thoughts would be greatly appreciated!Thanks a lot!

Use Excel pivot tables

IMHO I'd question why you need to have these dimensions and try to simplify the problem. Your strategy in the backtest drives the results from your input data. Assuming your strategy does not change for each dataset then it is the relationship between the datasets that may be more important and your backtest is merely a filter.The curse of dimensionality.I don't think you will find a straight answer to your question. I'd suggest trying to find a driver or dominant element in your data and focus on that.Once you get a good feel for that dimesion and how it changes others you can play with thought expirments to assist in visualising it.If you have an intuitive feel for the data you can then try to derive a formula to approximate it.FWIW I think you will find you have many dimensions in your backtest which drive entry and exit, understanding how these drive or filter your model may help you more than focusing on the final output.