jrmontag / STLDecompose

A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
MIT License
180 stars 49 forks source link

Consider a ramp-down of this library #16

Open jrmontag opened 5 years ago

jrmontag commented 5 years ago

It appears statsmodels has merged a PR to implement this years-old request! https://github.com/statsmodels/statsmodels/issues/4044 Since this library primarily extends the existing statsmodels internals, they will probably do this more robustly and flexibly.

For those currently using this library, there are no plans to delete this library! I've still got some net new things I'd like to do with it.

PabloIsCoding commented 5 years ago

I don't think this package does the stl decomposition as explained in the original paper. You should tell them this and revise it in my view.

Please do correct me if I'm mistaken, but the original algorithm is quite complex and your (as I remember it) is just a loess smoothing

Regards

Pablo

El mar., 16 jul. 2019 19:26, Josh Montague notifications@github.com escribió:

It appears statsmodels has merged a PR to implement this years-old request! statsmodels/statsmodels#4044 https://github.com/statsmodels/statsmodels/issues/4044 Since this library primarily extends the existing statsmodels internals, they will probably do this more robustly and flexibly.

For those currently using this library, there are no plans to delete this library! I've still got some net new things I'd like to do with it.

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jrmontag commented 4 years ago

As of v0.11 it looks like statsmodels has new STL functionality. Even more reason to try their version!