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adespatial (version 0.3-24)

Multivariate Multiscale Spatial Analysis

Description

Tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) .

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Install

install.packages('adespatial')

Monthly Downloads

4,847

Version

0.3-24

License

GPL (>= 2)

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Repository

https://github.com/adeverse/adespatial

Homepage

http://adeverse.github.io/adespatial/

Maintainer

Aurélie Siberchicot

Last Published

September 6th, 2024

Functions in adespatial (0.3-24)

aem.weight.edges

Weight edges when constructing AEM variables

TBI: Difference between multivariate observations at T1 and T2

Whittaker-Robinson periodogram

AEM for time series

Scotch Whiskey Data Set

constr.hclust-class

Class For Constrained Hiereachical Clustering

Space- And Time-Constrained Clustering

Bacterial production data set

create.dbMEM.model

Combine dbMEM matrices corresponding to groups of sites

directional.response

Directional indices of community change

Dissimilarity matrices for community composition data

dbMEM spatial eigenfunctions

Beta diversity computed as Var(Y)

Global and local tests

Interactive tool to generate R code that creates a spatial weighting matrix

forward.sel.par

Parametric forward selection of explanatory variables in regression and RDA

Mastigouche Lake network data set

Perform a test of the shared space-environment fraction of a variation partitioning using torus-translation (TT) or Moran Spectral Randomisation (MSR)

Compute the maximum distance of the minimum spanning tree based on a distance matrix

Decompose D in replacement and richness difference components

Function to compute and manage Moran's Eigenvector Maps (MEM) of a listw object

listw.candidates

Function to create a list of spatial weighting matrices

Function to choose a connection network

Function to optimize the selection of a spatial weighting matrix and select the best subset of eigenvectors (MEM, Moran's Eigenvector Maps)

Forward selection with multivariate Y using permutation under reducel model

Moran spectral randomization for variation partitioning

Moran spectral randomization for fourth-corner analysis

Function to compute Moran's index of spatial autocorrelation

moranNP.randtest

Function to compute positive and negative parts of Moran's index of spatial autocorrelation

Function to compute extreme values of Moran's I

msr.mantelrtest

Moran spectral randomization for Mantel test

Multi-frequential periodogram analysis

Moran spectral randomization

Selection of the best subset of spatial eigenvectors (MEM, Moran's Eigenvector Maps)

Multi-Scale Pattern Analysis

plot.orthobasisSp

Function to display Moran's Eigenvector Maps (MEM) and other spatial orthogonal bases

orthobasis.poly

Function to compute polynomial of geographical coordinates

Compute AIC for models with orthonormal explanatory variables

Rotate a set of point by a certain angle

Function to compute a scalogram

Space-time interaction in ANOVA without replication

Function to compute multivariate empirical variogram

tpaired.randtest

Permutational paired t-test

Trichoptera data set

Multivariate spatial analysis

Function to compute neighborhood based on the minimum spanning tree

Plots of the outputs of a temporal beta diversity analysis

plot.constr.hclust

Plotting Method For Space- And Time-Constrained Clustering

tpaired.krandtest

Paired t-tests of differences between T1 and T2 for each species

Function to compute and test eigenvectors of spatial weighting matrices

Contingency periodogram

Tiahura Transect Fish Data Set

Compute LCBD from any D matrix

aem.build.binary

Construct a site-by-edge binary matrix

Construct asymmetric eigenvector maps (AEM)