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astrogilda / tsbootstrap

tsbootstrap: generate bootstrapped time series samples in Python
https://tsbootstrap.readthedocs.io/en/latest/
MIT License
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Implement frequency-domain bootstrapping #107

Open astrogilda opened 7 months ago

astrogilda commented 7 months ago

Is your feature request related to a problem? Please describe. All extant methods are in the original time series domain. The package could benefit by adding complementary frequency-domain methods.

Describe the solution you'd like Some helpful papers (evolving list): 1 2

fkiraly commented 7 months ago

To me, this (at least the non-paywalled paper 2) reads like a pipeline or composite. That is transform -> bootstrap -> inverse_transform, where transform is fft, or transform (fft) -> transform (smoothe) -> bootstrap -> inverse_transform(fft)

Should we read this as a case for pipelines?

At least in sktime, where fft is already present, this pipeline could be easily built.