ate: Asymmetric temporal eigenfunctions

In gavinsimpson/temporalEF: Temporal Eigenfunctions

Description

Generate a set of asymmetric temporal eigenfunctions

Usage

ate(x, ...)

## Default S3 method:
ate(x, N, weight = FALSE, FUN = NULL, link0 = TRUE, ...)

## S3 method for class 'ate'
print(x, digits = 3, ...)

## S3 method for class 'ate'
scores(x, choices, ...)

## S3 method for class 'ate'
eigenvals(x, ...)

Arguments

x	an R object. For ate currently only a sorted vector of time points. For the print method an object of class "ate".
...	additional arguments passed to FUN.
N	numeric; the number of eigenvectors to return. If not supplied, N is taken from the appropriate dimension of x; for the default method, this is the length of x.
weight	logical; should a weighting matrix be generated and applied to the link matrix?
FUN	a function to be applied to the weighting matrix. Ignored if weight is FALSE.
link0	logical; should the link from t[0] be included?
digits	numeric; number of digits to display in output.
choices	numeric; vector indicating which eigenfunctions to return.

Details

The asymmetric eigenvector map (AEM) is a recently proposed method for describing orthongonal spatial functions for use in multivariate ordination. AEMs are asymmetric because they apply a directionality to the spatial dependencies modelled by the eigenfunctions. Asymmetric temporal eigenfunctions (ATEs) implement the AEM idea to model patterns of temporal dependence; i.e. a single spatial dimension.

Author(s)

Gavin L. Simpson

Examples

tp <- seq_len(10)
tefs <- ate(tp)
tefs.I <- moranI(tefs)
plot(tefs.I)

gavinsimpson/temporalEF documentation built on May 16, 2019, 10:11 p.m.