High-Dimensional Changepoint Estimation via Sparse Projection
Computing threshold used in inspect
MissCUSUM transformation of a matrix with missing entries
CUSUM transformation
MissCUSUM transformation of a single vector with missing entries
Informative sparse projection for estimation of changepoints (inspect)
Single changepoint estimation with missing data
Single changepoint estimation
Generating a high-dimensional time series with multiple changepoints
Matrix projection onto the nuclear norm unit sphere
Projection onto the standard simplex
Plot function for 'hdchangeseq' class
Plot function for 'inspect' class objects
Print function for 'inspect' class objects
Print percentage
Generate a random unit vectors in R^n
Noise standardisation for multivariate time series.
Generating high-dimensional time series with exactly one change in the...
Computing the sparse leading left singular vector of a matrix with mis...
Computing the sparse leading left singular vector of a matrix
Summary function for 'inspect' class objects
Clipping a vector from above and below
Norm of a vector
Normalise a vector
Soft thresholding a vector
Provides a data-driven projection-based method for estimating changepoints in high-dimensional time series. Multiple changepoints are estimated using a (wild) binary segmentation scheme.