FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data

Procedure for solving the maximin problem for identical design across heterogeneous data groups. Particularly efficient when the design matrix is either orthogonal or has tensor structure. Orthogonal wavelets can be specified for 1d, 2d or 3d data simply by name. For tensor structured design the tensor components (two or three) may be supplied. The package also provides an efficient implementation of the generic magging estimator.

Version: 1.0
Imports: Rcpp (≥ 0.12.12), glamlasso
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Published: 2022-05-12
Author: Adam Lund [aut, cre, ctb, cph], Benjamin Stephens [ctb, cph], Gael Guennebaud [ctb, cph], Angelo Furfaro [ctb, cph], Luca Di Gaspero [ctb, cph], Brandon Whitcher [ctb, cph]
Maintainer: Adam Lund <adam.lund at math.ku.dk>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
CRAN checks: FRESHD results

Documentation:

Reference manual: FRESHD.pdf

Downloads:

Package source: FRESHD_1.0.tar.gz
Windows binaries: r-devel: FRESHD_1.0.zip, r-release: FRESHD_1.0.zip, r-oldrel: FRESHD_1.0.zip
macOS binaries: r-release (arm64): FRESHD_1.0.tgz, r-oldrel (arm64): FRESHD_1.0.tgz, r-release (x86_64): FRESHD_1.0.tgz

Linking:

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