Package: kfino 1.0.0

kfino: Kalman Filter for Impulse Noised Outliers

A method for detecting outliers with a Kalman filter on impulsed noised outliers and prediction on cleaned data. 'kfino' is a robust sequential algorithm allowing to filter data with a large number of outliers. This algorithm is based on simple latent linear Gaussian processes as in the Kalman Filter method and is devoted to detect impulse-noised outliers. These are data points that differ significantly from other observations. 'ML' (Maximization Likelihood) and 'EM' (Expectation-Maximization algorithm) algorithms were implemented in 'kfino'. The method is described in full details in the following arXiv e-Print: <arxiv:2208.00961>.

Authors:Bertrand Cloez [aut], Isabelle Sanchez [aut, cre], Benedicte Fontez [ctr]

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6 exports 0.00 score 31 dependencies 6 scripts 138 downloads

Last updated 2 years agofrom:9571659564. Checks:OK: 3 NOTE: 4. Indexed: yes.

Exports:doutlierkfino_fitkfino_plotutils_EMutils_fitutils_likelihood

Dependencies:clicolorspacedplyrfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbletidyselectutf8vctrsviridisLitewithr