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Data Denoising with LOWESS (Locally Weighted Scatterplot Smoothing)
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:doc:`/SingleStepClassifiers/NonCausalStep/index`

This step applies the *LOWESS* algorithm to denoise the input time series data.

.. rubric:: Input Parameters

1. One-dimensional time series data

.. rubric:: Output Parameters

1. Denoised time series data

.. rubric:: Workflow

.. image:: workflow.svg


.. rubric:: Algorithm

:doc:`/Algorithms/LOWESS/index`

.. rubric:: References

- W.S.\  Cleveland, LOWESS: A program for smoothing scatterplots by robust locally weighted regression, The American Statistician, vol. 35 (1), pp. 54, 1981.

- W.S.\  Cleveland, Robust Locally Weighted Regression and Smoothing Scatterplots, Journal of the American Statistical Association, vol. 74 (368), pp. 829-836, 1979.

  `http://www.people.fas.harvard.edu/~gov2000/Handouts/lowess.pdf <http://www.people.fas.harvard.edu/~gov2000/Handouts/lowess.pdf>`__

- W.S.\  Cleveland, S.J. Devlin, Locally-Weighted Regression: An Approach to Regression Analysis by Local Fitting, Journal of the American Statistical Association, vol. 83 (403), pp. 596-610, 1988.

  `http://www.econ.pdx.edu/faculty/KPL/readings/cleveland88.pdf <http://www.econ.pdx.edu/faculty/KPL/readings/cleveland88.pdf>`__