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onlineCPD (version 1.0)

Detect Changepoints in Multivariate Time Series

Description

Detects multiple changepoints in uni- or multivariate time series data. The algorithm is based on Bayesian methods and detects changes on-line; i.e. the model updates with every observation rather than relying on retrospective segmentation. However, the user may choose to use the algorithm off- or on-line.

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Version

Install

install.packages('onlineCPD')

Monthly Downloads

3

Version

1.0

License

GPL-3

Maintainer

Zachary Zanussi

Last Published

August 23rd, 2016

Functions in onlineCPD (1.0)

print.oCPD

Summarizing oCPD results
WalBelSentiment

Sentiment and Emotion Annotated Twitter Data from the Wales versus Belgium 2016 Euro Cup Soccer Game
offlineCPD

Offline Bayesian Changepoint Detection
plot.oCPD

Plotting onlineCPD results
studentpdf

Student Probability Density Function
onlineCPD

Online Changepoint Detection
const_hazard

Constant Hazard Function
onlineCPD-package

onlineCPD
findCP

Wisely Pick Changepoints