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Weekly Report -- 27/04/2012




Managed to master the art of wavelet transforms - the problems I was having was due to mismatching the scale and wavelet values when inverting the transformation. After a lot of debugging, I was able to ensure that I could reliably transform my data and then invert it back to the same original values for any given number of nested transformations. Once that was working, I was able to get sensible results when denoising my time series.

Now that I had a denoised time series, I turned back to looking at forecasting techniques. Holt-Winters still wasn't a good fit for the denoised data, so I started learning about ARIMA models. Unfortunately, the test data I have doesn't really fit the basic ARIMA models, which made it difficult to get the right fit. Anyway, I now have a decent understanding of how ARIMA works in general, but need to come up with a way to use the ARIMA model in an on-line, self-updating context.

Released libprotoident 2.0.5 on Friday, mainly as something to do so I could have a break from mathematics for a bit :)