ACE and AVAS for Selecting Multiple Regression Transformations
Released Oct 29, 2016 by Phil Spector, Jerome Friedman, Robert Tibshirani, Thomas Lumley, Shawn Garbett, Jonathan Baron
Two nonparametric methods for multiple regression transform selection are provided. The first, Alternative Conditional Expectations (ACE), is an algorithm to find the fixed point of maximal correlation, i.e. it finds a set of transformed response variables that maximizes R^2 using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations for Multiple Regression and Correlation". Journal of the American Statistical Association. 80:580-598.
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>acepack</artifactId> <version>1.4.1-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>
If you're using Renjin from the command line, you load this library by invoking:
This package was last tested against Renjin 0.8.2523 on Nov 11, 2017.