README.md
In gavinsimpson/temporalEF: Temporal Eigenfunctions
temporalEF
Released version
Build status
What is temporalEF?
temporalEF is an R package that computes eigenfunctions for use in
explaining patterns in multivariate time series. The basic idea is taken
from recent developments in the field of spatial analysis in multivariate
data sets.
Principal coordinates of neighbour matrices (PCNM) and the more recent
Asymmetric eigenvector maps (AEM) were designed to model variation at
multiple spatial scales. temporalEF utilises these methods by taking
the time direction as a one-dimensional spatial process. The resulting
eigenfunctions represent sinusoidal functions of varying periodicity.
The resulting eigenfunctions can be used in constrained ordinations such
as redundancy analysis (RDA), canonical correspondence analysis (CCA),
or constrained analysis of principal coordinates (CAP) to decompose a
species data matrix into independent patterns of temporal variation or
trends.
Installation
The simplest way to install temporalEF is to use the devtools package
devtools::install_github("gavinsimpson/temporalEF")
Licence
temporalEF is made available under the GNU GPL version 2
licence.
gavinsimpson/temporalEF documentation built on May 16, 2019, 10:11 p.m.
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temporalEF
Released version
Build status
What is temporalEF?
temporalEF is an R package that computes eigenfunctions for use in explaining patterns in multivariate time series. The basic idea is taken from recent developments in the field of spatial analysis in multivariate data sets.
Principal coordinates of neighbour matrices (PCNM) and the more recent Asymmetric eigenvector maps (AEM) were designed to model variation at multiple spatial scales. temporalEF utilises these methods by taking the time direction as a one-dimensional spatial process. The resulting eigenfunctions represent sinusoidal functions of varying periodicity.
The resulting eigenfunctions can be used in constrained ordinations such as redundancy analysis (RDA), canonical correspondence analysis (CCA), or constrained analysis of principal coordinates (CAP) to decompose a species data matrix into independent patterns of temporal variation or trends.
Installation
The simplest way to install temporalEF is to use the devtools package
devtools::install_github("gavinsimpson/temporalEF")
Licence
temporalEF is made available under the GNU GPL version 2 licence.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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