CRAN

diffMeshGP 0.1.0

Multi-Fidelity Computer Experiments Using the Tuo-Wu-Yu Model

Released May 12, 2017 by Wenjia Wang

This package can be loaded by Renjin but all tests failed.

This R function implements the nonstationary Kriging model proposed by Tuo, Wu and Yu (2014) for analyzing multi-fidelity computer outputs. This function computes the maximum likelihood estimates for the model parameters as well as the predictive means and variances of the exact solution (i.e., the conceptually highest fidelity).

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>diffMeshGP</artifactId>
    <version>0.1.0-b15</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:diffMeshGP')

Test Results

This package was last tested against Renjin 0.9.2689 on Aug 26, 2018.

GPdiffMesh-examples

Source

View GitHub Mirror

Release History

0.1.0