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.
Package details |
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Author | Pedro J. Leitão, Marcel Schwieder, Cornelius Senf |
Maintainer | Pedro J. Leitão <steppebird@gmail.com>, Cornelius Senf <corneliussenf@googlemail.de> |
License | GPL-3 |
Version | 1.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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