Other packages > Find by keyword >

OLCPM  

Online Change Point Detection for Matrix-Valued Time Series
View on CRAN: Click here


Download and install OLCPM package within the R console
Install from CRAN:
install.packages("OLCPM")

Install from Github:
library("remotes")
install_github("cran/OLCPM")

Install by package version:
library("remotes")
install_version("OLCPM", "0.1.2")



Attach the package and use:
library("OLCPM")
Maintained by
Long Yu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-02-27
Latest Update: 2024-05-30
Description:
We provide two algorithms for monitoring change points with online matrix-valued time series, under the assumption of a two-way factor structure. The algorithms are based on different calculations of the second moment matrices. One is based on stacking the columns of matrix observations, while another is by a more delicate projected approach. A well-known fact is that, in the presence of a change point, a factor model can be rewritten as a model with a larger number of common factors. In turn, this entails that, in the presence of a change point, the number of spiked eigenvalues in the second moment matrix of the data increases. Based on this, we propose two families of procedures - one based on the fluctuations of partial sums, and one based on extreme value theory - to monitor whether the first non-spiked eigenvalue diverges after a point in time in the monitoring horizon, thereby indicating the presence of a change point. This package also provides some simple functions for detecting and removing outliers, imputing missing entries and testing moments. See more details in He et al. (2021).
How to cite:
Long Yu (2023). OLCPM: Online Change Point Detection for Matrix-Valued Time Series. R package version 0.1.2, https://cran.r-project.org/web/packages/OLCPM. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.1.0 (2023-02-27 09:52), 0.1.1 (2024-02-05 13:00)
Other packages that cited OLCPM R package
View OLCPM citation profile
Other R packages that OLCPM depends, imports, suggests or enhances
Complete documentation for OLCPM
Functions, R codes and Examples using the OLCPM R package
Full OLCPM package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

msm  
Multi-State Markov and Hidden Markov Models in Continuous Time
Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal d ...
Download / Learn more Package Citations See dependency  
envirem  
Generation of ENVIREM Variables
Generation of bioclimatic rasters that are complementary to the typical 19 bioclim variables. ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
crossurr  
Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers
Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebau ...
Download / Learn more Package Citations See dependency  
ibb  
R Wrapper for Istanbul Municipality Open Data Portal
Call wrappers for Istanbul Metropolitan Municipality's Open Data Portal (Turkish: Istanbul B ...
Download / Learn more Package Citations See dependency  

27,268

R Packages

233,548

Dependencies

72,590

Author Associations

27,205

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA