Anderson-Darling K-Sample Test and Combinations of Such Tests
Released Oct 29, 2012 by Fritz Scholz
The Anderson-Darling K-sample test can be used to test whether several independent random samples of various sizes come from the same but unspecified continuous distribution. It is a rank test and consistent against all alternatives. A low to moderate number of tied observations can be tolerated. The combination of such tests can be used to test whether M groups of samples (with K allowed to vary from group to group) come from respective common distributions, which may vary from group to group. This is useful in testing for treatment effects in randomized (incomplete) block designs or in examining whether several laboratories perform equally well when asked to measure a sufficient number of test speciments from different batches or materials.
This package can be included as a dependency from a Java or Scala project by including
the following your project's
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>adk</artifactId> <version>1.0-2-b232</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
If you're using Renjin from the command line, you load this library by invoking:
This package was last tested against Renjin 0.8.2359 on May 26, 2017.