online.network.missing {changepoints}

Online change point detection for network data with missing values.

Description

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

Usage

online.network.missing(
  data_incomplete_list,
  eta_list,
  alpha_grid,
  thresholds_array,
  rho_hat,
  pi_ub_hat,
  C_lambda = 2/3,
  delta = 5
)

Arguments

data_incomplete_list

A list of adjacency matrices (with entries being 0 or 1) with missing values being coercing to 0.

eta_list

A list of matrices associated with data_incomplete_list, each matrix indicates the missing entries in corresponding adjacency matrix.

alpha_grid

A numeric vector in (0,1) representing the desired false alarm rate.

thresholds_array

A numeric array of calibrated thresholds.

rho_hat

A numeric scalar of the sparsity parameter.

pi_ub_hat

A numeric scalar of the upper bound of the missing probability.

C_lambda

A numeric scalar of an absolute constant, which is set to be 2/3 by default.

delta

An integer scalar of minimum spacing.

Value

Online change point estimator.

Author(s)

Haotian Xu

References

Dubey, Xu and Yu (2021) <arxiv:2110.06450>

See Also

calibrate.online.network.missing for calibrating thresholds.