online.network.missing

Perform online change point detection for network with missing values by controlling the false alarm rate at level alpha.

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

online.network.missing function

<dl><dt>data_incomplete_list</dt>
<dd>A <code>list</code> of adjacency matrices (with entries being 0 or 1) with missing values being coercing to 0.</dd>
<dt>eta_list</dt>
<dd>A <code>list</code> of matrices associated with data_incomplete_list, each matrix indicates the missing entries in corresponding adjacency matrix.</dd>
<dt>alpha_grid</dt>
<dd>A <code>numeric</code> vector in (0,1) representing the desired false alarm rate.</dd>
<dt>thresholds_array</dt>
<dd>A <code>numeric</code> array of calibrated thresholds.</dd>
<dt>rho_hat</dt>
<dd>A <code>numeric</code> scalar of the sparsity parameter.</dd>
<dt>pi_ub_hat</dt>
<dd>A <code>numeric</code> scalar of the upper bound of the missing probability.</dd>
<dt>C_lambda</dt>
<dd>A <code>numeric</code> scalar of an absolute constant, which is set to be 2/3 by default.</dd>
<dt>delta</dt>
<dd>An <code>integer</code> scalar of minimum spacing.</dd></dl>

Arguments

Author

Online change point detection for network data with missing values. — online.network.missing

<dl>

<dt>data_incomplete_list</dt>
<dd>A <code>list</code> of adjacency matrices (with entries being 0 or 1) with missing values being coercing to 0.</dd>


<dt>eta_list</dt>
<dd>A <code>list</code> of matrices associated with data_incomplete_list, each matrix indicates the missing entries in corresponding adjacency matrix.</dd>


<dt>alpha_grid</dt>
<dd>A <code>numeric</code> vector in (0,1) representing the desired false alarm rate.</dd>


<dt>thresholds_array</dt>
<dd>A <code>numeric</code> array of calibrated thresholds.</dd>


<dt>rho_hat</dt>
<dd>A <code>numeric</code> scalar of the sparsity parameter.</dd>


<dt>pi_ub_hat</dt>
<dd>A <code>numeric</code> scalar of the upper bound of the missing probability.</dd>


<dt>C_lambda</dt>
<dd>A <code>numeric</code> scalar of an absolute constant, which is set to be 2/3 by default.</dd>


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

</dl>

online.network.missing: Online change point detection for network data with missing values.

Description

Usage

Value

Arguments

Author

References

See Also