Kalman Filter for Impulse Noised Outliers
doutlier defines an outlier distribution (Surface of a trapezium) and ...
kfino: Kalman Filtering
kfino_fit a function to detect outlier with a Kalman Filtering approac...
kfino_plot a graphical function for the result of a kfino run
utils_EM a function to estimate the parameters m_0 , mm, pp thro...
utils_fit a fonction running the kfino algorithm to filter data and de...
utils_likelihood a function to calculate a likelihood on initial param...
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>.
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