Nonparametric kernel estimation of the distribution function. Bandwidth selection and estimation of related functions.
Released Aug 13, 2012 by Alejandro Quintela del Rio
Nonparametric kernel distribution function estimation is performed. Three automatic bandwidth selection methods for nonparametric kernel distribution function estimation are implemented: the plug-in of Altman and Leger, the plug-in of Polansky and Baker, and the modified cross-validation of Bowman, Hall and Prvan. The exceedance function, the mean return period and the return level are also computed.
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>kerdiest</artifactId> <version>1.2-b279</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 0.9.2687 on Aug 25, 2018.