Package: FRESHD
Type: Package
Title: Fast Robust Estimation of Signals in Heterogeneous Data
Version: 1.0
Date: 2022-05-09
Authors@R: c(person(given = "Adam",
             family = "Lund",
             role = c("aut", "cre", "ctb", "cph"),
             email = "adam.lund@math.ku.dk"),
             person(given = "Benjamin",
             family = "Stephens",
             role = c("ctb", "cph")),
             person(given = "Gael",
             family = "Guennebaud",
             role = c("ctb", "cph")),
             person(given = "Angelo",
             family = "Furfaro",
             role = c("ctb", "cph")),
             person(given = "Luca",
             family = "Di Gaspero",
             role = c("ctb", "cph")),
             person(given = "Brandon",
             family = "Whitcher",
             role = c("ctb", "cph")))
Maintainer: Adam Lund <adam.lund@math.ku.dk>
Description: 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.
Imports: Rcpp (>= 0.12.12), glamlasso
License: GPL
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
RoxygenNote: 7.1.2
NeedsCompilation: yes
Packaged: 2022-05-10 18:35:57 UTC; adam
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]
Repository: CRAN
Date/Publication: 2022-05-12 08:00:06 UTC
Built: R 4.4.0; aarch64-apple-darwin20; 2024-04-06 04:32:08 UTC; unix
Archs: FRESHD.so.dSYM
