kfino

Kalman Filter for Impulse Noised Outliers

CRAN Package

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: doi:10.48550/arXiv.2208.00961.

  • Version1.0.0
  • R versionunknown
  • LicenseGPL-3
  • Needs compilation?No
  • Last release11/03/2022

Documentation


Team


Insights

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Imports2 packages
  • Suggests6 packages