Package: FRESHD 1.0
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.
Authors:
FRESHD_1.0.tar.gz
FRESHD_1.0.tar.gz(r-4.5-noble)FRESHD_1.0.tar.gz(r-4.4-noble)
FRESHD_1.0.tgz(r-4.4-emscripten)FRESHD_1.0.tgz(r-4.3-emscripten)
FRESHD.pdf |FRESHD.html✨
FRESHD/json (API)
# Install 'FRESHD' in R: |
install.packages('FRESHD', repos = 'https://cloud.r-project.org') |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:62d6c26fa0. Checks:1 OK, 1 NOTE. Indexed: no.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Feb 18 2025 |
R-4.5-linux-x86_64 | NOTE | Feb 18 2025 |
Dependencies:glamlassoRcppRcppArmadilloRcppEigen
Citation
To cite package ‘FRESHD’ in publications use:
Lund A (2022). FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data. R package version 1.0, https://CRAN.R-project.org/package=FRESHD.
Corresponding BibTeX entry:
@Manual{, title = {FRESHD: Fast Robust Estimation of Signals in Heterogeneous Data}, author = {Adam Lund}, year = {2022}, note = {R package version 1.0}, url = {https://CRAN.R-project.org/package=FRESHD}, }
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Inverse discrete wavelet transform | iwt |
Maximin Aggregation | magging |
Maximin signal estimation | FRESHD maximin |
Make Prediction From a FRESHD Object | FRESHD.predict FRESHD_predict predict.FRESHD |
Print Function for objects of Class FRESHD | print.FRESHD |
The Rotated H-transform of a 3d Array by a Matrix | FRESHD_RH H RH Rotate |
Discrete wavelet transform | wt |