java-timeseries
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Time series analysis in Java
Hi, @signaflo ! Sorry to bother you. I have to say you've done so wonderful work that it helped a lot on ARIMA. As you know , there are so...
The ARIMA models should be able to automatically apply a supplied one parameter [Box-Cox transformation](https://en.wikipedia.org/wiki/Power_transform#Box%E2%80%93Cox_transformation) when fitting the model. When the model is forecast, the Box-Cox transformation should be reversed...
Any non-invertible MA model can be converted to an invertible one, except when the roots lie exactly on the unit circle. The algorithm for doing so first needs to be...
Clients should be able to see whether the model they built is causal, stationary, and invertible.
Currently, one needs to provide the complete time series, in order to build an ARIMA model and subsequently obtain forecasts. When used in a streaming application, so that the time...
Hi, I use your library in a streaming environment to generate an ARIMA based time series. The simulated time series is supposed to be very long (possibly infinite). Unfortunately, the...
See discussion in PR https://github.com/signaflo/java-timeseries/pull/3 Code ``` while (!(Double.isFinite(functionValue) && functionValue < priorFunctionValue + C1 * stepSize * slopeAt0) && !stop) { ```` can fall into infinite loop.
I am making ARIMA predictions with yearly seasonality and data. with 24 months of history, the prediction is as good as cn be expected with s little data, but if...