Hello, I was doing some work with Kalman Filters recently, and I noticed the implementation in commons.math is missing a couple of features, namely smoothing and model-fitting.
Would it be good to add these? A little bit more on the model and the proposed features: The Kalman Filter is a model for time-series data. The version in commons.maths can do prediction (i.e. given the state now, predict the next state). The algorithm can also do smoothing (given a sequence of data, perhaps with gaps, estimate the most likely state at each step) -- but this version doesn't have an implementation. Also, given a time-series dataset, you can fit a Kalman Filter. There isn't a precise solution, but using expectation maximisation works well. I am new to the Apache Commons mailing list -- please forgive me if this is the wrong way to go about things. Kind regards, - Daniel -- -------------------------------------- Dr Daniel Winterstein Director Edinburgh +44 (0)772 5172 612 http://sodash.com http://sogrow.co.uk --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@commons.apache.org For additional commands, e-mail: dev-h...@commons.apache.org
