lookout-package

<img src="figures/logo.png?package=lookout&version=0.1.4" style="float: right" alt="logo" width="120">
Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.

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Outlier detection using leave-one-out kernel density estimates and
extreme value theory. The bandwidth for kernel density estimates is computed
using persistent homology, a technique in topological data analysis. Using
peak-over-threshold method, a generalized Pareto distribution is fitted to
the log of leave-one-out kde values to identify outliers.

Sevvandi Kandanaarachchi

lookout

Leave One Out Kernel Density Estimates for Outlier Detection

Rob Hyndman

Chris Fraley

lookout-package function

Maintainer: Sevvandi Kandanaarachchi <a href="/link/sevvandik%40gmail.com?package=lookout&version=0.1.4" data-mini-rdoc="lookout::sevvandik@gmail.com">sevvandik@gmail.com</a> (<a href="https://orcid.org/0000-0002-0337-0395">ORCID</a>)
Authors:<ul>
<li>Rob Hyndman <a href="/link/rob.hyndman%40monash.edu?package=lookout&version=0.1.4" data-mini-rdoc="lookout::rob.hyndman@monash.edu">rob.hyndman@monash.edu</a> (<a href="https://orcid.org/0000-0002-2140-5352">ORCID</a>)</li>
</ul>Other contributors:<ul>
<li>Chris Fraley <a href="/link/fraley%40u.washington.edu?package=lookout&version=0.1.4" data-mini-rdoc="lookout::fraley@u.washington.edu">fraley@u.washington.edu</a> [contributor]</li>
</ul>

Author

<img src='figures/logo.png' style='float: right' alt='logo' width='120' />
Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.

lookout: Leave One Out Kernel Density Estimates for Outlier Detection — lookout-package

Maintainer: Sevvandi Kandanaarachchi <a href='mailto:sevvandik@gmail.com'>sevvandik@gmail.com</a> (<a href='https://orcid.org/0000-0002-0337-0395'>ORCID</a>)
Authors:<ul>
<li>Rob Hyndman <a href='mailto:rob.hyndman@monash.edu'>rob.hyndman@monash.edu</a> (<a href='https://orcid.org/0000-0002-2140-5352'>ORCID</a>)</li>
</ul>

Other contributors:<ul>
<li>Chris Fraley <a href='mailto:fraley@u.washington.edu'>fraley@u.washington.edu</a> [contributor]</li>
</ul>

lookout-package: lookout: Leave One Out Kernel Density Estimates for Outlier Detection

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