CRAN

not 1.0

Narrowest-Over-Threshold Change-Point Detection

Released Aug 23, 2016 by Rafal Baranowski

Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following 'deterministic signal + noise' model. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>not</artifactId>
    <version>1.0-b25</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:not')

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 1, 2018.

• aic.penalty-examples
• features-examples
• loglik.not-examples
• not-examples
• plot.not-examples
• predict.not-examples
• random.intervals-examples
• residuals.not-examples
• sic.penalty-examples

Source

View GitHub Mirror

Release History

• 1.0