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R Package implementing the CVE (Conditional Variance Estimation) Method for SDR (Sufficient Dimension Reduction).
47 Commits 1 Branch 2 Tags 5 MiB
R 57.8%
C 42.2%
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Daniel Kapla 05c2aea44a add: multivariate Y (aka projective resampling) 2020-09-17 18:27:31 +02:00
CVE add: multivariate Y (aka projective resampling) 2020-09-17 18:27:31 +02:00
simulations - add: simulations, 2019-12-17 12:07:33 +01:00
README.md Fix urls to release files after server upgrade 2020-01-06 10:19:08 +00:00
cve_tensorflow.R add: multivariate Y (aka projective resampling) 2020-09-17 18:27:31 +02:00

README.md

Installation Instructions

The package depends on the mda package (see: mda @ cran.r-project. Therefore the first step is to install the mda package

install.packages("mda")

A release will be available in a few days.

Open R and then the following:

# addapt to download file.
install.packages("path/to/cve_0.2.<end>", repos = NULL)
library(CVE) # Test installation.

Please consult the man-pages ?install.package and ?library for further information.

Installing Source

Cloning the CVE repository and using R's build and install routines from a terminal.

git clone https://git.art-ist.cc/daniel/CVE.git  # Clone repository
cd CVE                                           # Go into the repository
R CMD build CVE                                  # Build package tarbal
R CMD INSTALL CVE_0.2.tar.gz                     # Install package

Windows / macOS

Installing from source (for any package which contains compiled code, in our case C) on Windows and MacOS requires additional tools. See R Installation and Administration from r-project manuals.

Repository Structure

The repository is structured in two directories, the CVE/ directory which is the R package root and simulations/ where all simulation scripts can be found (and README.md which is this).