sparsegdm/sgdm_package: Package for performing sparse generalized dissimilarity model including tools for gdm

Sparse generalized dissimilarity modeling (SGDM) is a two-stage method consisting of initially reducing the environmental data by means of a sparse canonical correlation analysis, to then fit the resulting sparse canonical components in a generalized dissimilarity model (GDM). The package also includes additional tools, useful for both GDM and SGDM.

Getting started

Package details

AuthorPedro J. Leitão, Marcel Schwieder, Cornelius Senf
MaintainerPedro J. Leitão <steppebird@gmail.com>, Cornelius Senf <corneliussenf@googlemail.de>
LicenseGPL-3
Version1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("sparsegdm/sgdm_package")
sparsegdm/sgdm_package documentation built on May 30, 2019, 6:35 a.m.