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Provides graph-constrained regression methods in which regularization parameters are selected automatically via estimation of equivalent Linear Mixed Model formulation. 'riPEER' (ridgified Partially Empirical Eigenvectors for Regression) method employs a penalty term being a linear combination of graph-originated and ridge-originated penalty terms, whose two regularization parameters are ML estimators from corresponding Linear Mixed Model solution; a graph-originated penalty term allows imposing similarity between coefficients based on graph information given whereas additional ridge-originated penalty term facilitates parameters estimation: it reduces computational issues arising from singularity in a graph-originated penalty matrix and yields plausible results in situations when graph information is not informative. 'riPEERc' (ridgified Partially Empirical Eigenvectors for Regression with constant) method utilizes addition of a diagonal matrix multiplied by a predefined (small) scalar to handle the non-invertibility of a graph Laplacian matrix. 'vrPEER' (variable reducted PEER) method performs variable-reduction procedure to handle the non-invertibility of a graph Laplacian matrix.
Version: | 1.0.1 |
Depends: | R (≥ 3.3.3) |
Imports: | reshape2, ggplot2, nlme, boot, nloptr, rootSolve, psych, magic, glmnet |
Suggests: | knitr, rmarkdown |
Published: | 2017-05-30 |
DOI: | 10.32614/CRAN.package.mdpeer |
Author: | Marta Karas [aut, cre], Damian Brzyski [ctb], Jaroslaw Harezlak [ctb] |
Maintainer: | Marta Karas <marta.karass at gmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | mdpeer results |
Reference manual: | mdpeer.pdf |
Vignettes: |
Intro and usage examples |
Package source: | mdpeer_1.0.1.tar.gz |
Windows binaries: | r-devel: mdpeer_1.0.1.zip, r-release: mdpeer_1.0.1.zip, r-oldrel: mdpeer_1.0.1.zip |
macOS binaries: | r-release (arm64): mdpeer_1.0.1.tgz, r-oldrel (arm64): mdpeer_1.0.1.tgz, r-release (x86_64): mdpeer_1.0.1.tgz, r-oldrel (x86_64): mdpeer_1.0.1.tgz |
Old sources: | mdpeer archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.