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A direct and flexible method for estimating an ICA model. This approach estimates the densities for each component directly via a tilted Gaussian. The tilt functions are estimated via a GAM Poisson model. Details can be found in "Elements of Statistical Learning (2nd Edition)" in Section 14.7.4.
| Version: | 1.1 |
| Depends: | gam |
| Published: | 2022-02-21 |
| Author: | Trevor Hastie, Rob Tibshirani |
| Maintainer: | Trevor Hastie <hastie at stanford.edu> |
| License: | GPL-2 |
| URL: | https://hastie.su.domains/ElemStatLearn/printings/ESLII_print12_toc.pdf |
| NeedsCompilation: | no |
| CRAN checks: | ProDenICA results |
| Reference manual: | ProDenICA.pdf |
| Package source: | ProDenICA_1.1.tar.gz |
| Windows binaries: | r-devel: ProDenICA_1.1.zip, r-release: ProDenICA_1.1.zip, r-oldrel: ProDenICA_1.1.zip |
| macOS binaries: | r-release (arm64): ProDenICA_1.1.tgz, r-oldrel (arm64): ProDenICA_1.1.tgz, r-release (x86_64): ProDenICA_1.1.tgz, r-oldrel (x86_64): ProDenICA_1.1.tgz |
| Old sources: | ProDenICA archive |
| Reverse suggests: | steadyICA |
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These binaries (installable software) and packages are in development.
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