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: 2024-02-05
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 23 Nov. 2024.
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
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

abcADM  
Fit Accumulated Damage Models and Estimate Reliability using ABC
Estimate parameters of accumulated damage load duration models based on failure time data under a Ba ...
Download / Learn more Package Citations See dependency  
highlight  
Syntax Highlighter
Syntax highlighter for R code based on the results of the R parser. Rendering in HTML and latex mar ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
Mondrian  
A Simple Graphical Representation of the Relative Occurrence and Co-Occurrence of Events
The unique function of this package allows representing in a single graph the relative occurrence an ...
Download / Learn more Package Citations See dependency  
triplot  
Explaining Correlated Features in Machine Learning Models
Tools for exploring effects of correlated features in predictive models. The predict_triplot() func ...
Download / Learn more Package Citations See dependency  
Simile  
Interact with Simile Models
Allows a Simile model saved as a compiled binary to be loaded, parameterized, executed and interroga ...
Download / Learn more Package Citations See dependency  

23,229

R Packages

199,929

Dependencies

62,984

Author Associations

23,230

Publication Badges

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