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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. <doi:10.1080/01621459.1985.10478157>]. Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when correlation is low [see Tibshirani, R.. 1986. "Estimating Transformations for Regression via Additivity and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. <doi:10.1080/01621459.1988.10478610>]. A good introduction to these two methods is in chapter 16 of Frank Harrel's "Regression Modeling Strategies" in the Springer Series in Statistics.
| Version: | 1.4.2 |
| Suggests: | testthat |
| Published: | 2023-08-22 |
| DOI: | 10.32614/CRAN.package.acepack |
| Author: | Phil Spector, Jerome Friedman, Robert Tibshirani, Thomas Lumley, Shawn Garbett, Jonathan Baron |
| Maintainer: | Shawn Garbett <shawn.garbett at vumc.org> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | acepack results |
| Reference manual: | acepack.pdf |
| Package source: | acepack_1.4.2.tar.gz |
| Windows binaries: | r-devel: acepack_1.4.2.zip, r-release: acepack_1.4.2.zip, r-oldrel: acepack_1.4.2.zip |
| macOS binaries: | r-release (arm64): acepack_1.4.2.tgz, r-oldrel (arm64): acepack_1.4.2.tgz, r-release (x86_64): acepack_1.4.2.tgz, r-oldrel (x86_64): acepack_1.4.2.tgz |
| Old sources: | acepack archive |
| Reverse depends: | nlts |
| Reverse imports: | lancor, stops |
| Reverse suggests: | bullseye, Hmisc |
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