CRAN

GaussianHMM1d 1.0.1

Inference, Goodness-of-Fit and Forecast for Univariate Gaussian Hidden Markov Models

Released Mar 7, 2019 by Bouchra Nasri

Dependencies

doParallel 1.0.14 foreach 1.4.4

Inference, goodness-of-fit test, and prediction densities and intervals for univariate Gaussian Hidden Markov Models (HMM). The goodness-of-fit is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Chapter 10.2 of Remillard (2013) .

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>GaussianHMM1d</artifactId>
    <version>1.0.1-b1</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:GaussianHMM1d')

Test Results

This package was last tested against Renjin 0.9.2724 on Mar 9, 2019.

• EstHMM1d-examples
• EstRegime-examples
• ForecastHMMPdf-examples
• ForecastHMMeta-examples
• GaussianMixtureCdf-examples
• GaussianMixtureInv-examples
• GaussianMixturePdf-examples
• Sim.HMM.Gaussian.1d-examples
• Sim.Markov.Chain-examples
• bootstrapfun-examples
• em.step-examples

Source

View GitHub Mirror

Release History

• 1.0.1