WBS.uni.rob

Perform a robust version of the wild binary segmentation method using Huber loss.

Performs a series of offline and/or online change-point detection algorithms for 1) univariate mean: <doi:10.1214/20-EJS1710>, <arXiv:2006.03283>; 2) univariate polynomials: <doi:10.1214/21-EJS1963>; 3) univariate and multivariate nonparametric settings: <doi:10.1214/21-EJS1809>, <doi:10.1109/TIT.2021.3130330>; 4) high-dimensional covariances: <doi:10.3150/20-BEJ1249>; 5) high-dimensional networks with and without missing values: <doi:10.1214/20-AOS1953>, <arXiv:2101.05477>, <arXiv:2110.06450>; 6) high-dimensional linear regression models: <arXiv:2010.10410>, <arXiv:2207.12453>; 7) high-dimensional vector autoregressive models: <arXiv:1909.06359>; 8) high-dimensional self exciting point processes: <arXiv:2006.03572>; 9) dependent dynamic nonparametric random dot product graphs: <arXiv:1911.07494>; 10) univariate mean against adversarial attacks: <arXiv:2105.10417>.

Haotian Xu

changepoints

A Collection of Change-Point Detection Methods

Oscar Padilla

Daren Wang

Mengchu Li

Qin Wen

WBS.uni.rob function

<dl><dt>y</dt>
<dd>A <code>numeric</code> vector of observations.</dd>
<dt>s</dt>
<dd>A <code>numeric</code> scalar representing the starting index of an interval.</dd>
<dt>e</dt>
<dd>A <code>numeric</code> scalar representing the ending index of an interval.</dd>
<dt>Alpha</dt>
<dd>An <code>integer</code> vector of starting indices of random intervals.</dd>
<dt>Beta</dt>
<dd>An <code>integer</code> vector of ending indices of random intervals.</dd>
<dt>K</dt>
<dd>A <code>numeric</code> scalar representing the robustification parameter in the Huber loss.</dd>
<dt>delta</dt>
<dd>A positive <code>integer</code> scalar of minimum spacing.</dd>
<dt>level</dt>
<dd>Should be fixed as 0.</dd></dl>

Arguments

Author

Robust wild binary segmentation for univariate mean change points detection. — WBS.uni.rob

<dl>

<dt>y</dt>
<dd>A <code>numeric</code> vector of observations.</dd>


<dt>s</dt>
<dd>A <code>numeric</code> scalar representing the starting index of an interval.</dd>


<dt>e</dt>
<dd>A <code>numeric</code> scalar representing the ending index of an interval.</dd>


<dt>Alpha</dt>
<dd>An <code>integer</code> vector of starting indices of random intervals.</dd>


<dt>Beta</dt>
<dd>An <code>integer</code> vector of ending indices of random intervals.</dd>


<dt>K</dt>
<dd>A <code>numeric</code> scalar representing the robustification parameter in the Huber loss.</dd>


<dt>delta</dt>
<dd>A positive <code>integer</code> scalar of minimum spacing.</dd>


<dt>level</dt>
<dd>Should be fixed as 0.</dd>

</dl>

WBS.uni.rob: Robust wild binary segmentation for univariate mean change points detection.

Description

Usage

Value

Arguments

Author

References

See Also