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adespatial (version 0.3-29)

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

7,350

Version

0.3-29

License

GPL (>= 2)

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Repository

https://github.com/adeverse/adespatial

Homepage

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

Maintainer

Aurélie Siberchicot

Last Published

March 21st, 2026

Functions in adespatial (0.3-29)

dbMEM spatial eigenfunctions

Dissimilarity matrices for community composition data

directional.response

Directional indices of community change

Bacterial production data set

Beta diversity computed as Var(Y)

Decompose D in replacement and richness difference components

constr.hclust-class

Class For Constrained Hiereachical Clustering

create.dbMEM.model

Combine dbMEM matrices corresponding to groups of sites

Function to choose a connection network

Space- And Time-Constrained Clustering

listw.candidates

Function to create a list of spatial weighting matrices

Geodetic Distances from Latitude and Longitude

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

Geodetic Coordinates from Latitude and Longitude

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

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

forward.sel.par

Parametric forward selection of explanatory variables in regression and RDA

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

Forward selection with multivariate Y using permutation under reducel model

Global and local tests

Multi-Scale Pattern Analysis

Multi-frequential periodogram analysis

Function to compute extreme values of Moran's I

Moran spectral randomization for fourth-corner analysis

Mastigouche Lake network data set

Moran spectral randomization

moranNP.randtest

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

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

Function to compute Moran's index of spatial autocorrelation

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

Moran spectral randomization for variation partitioning

Compute AIC for models with orthonormal explanatory variables

plot.orthobasisSp

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

Plots of the outputs of a temporal beta diversity analysis

plot.constr.hclust

Plotting Method For Space- And Time-Constrained Clustering

Rotate a set of point by a certain angle

orthobasis.poly

Function to compute polynomial of geographical coordinates

Function to compute neighborhood based on the minimum spanning tree

msr.mantelrtest

Moran spectral randomization for Mantel test

Multivariate spatial analysis

Trichoptera data set

tpaired.randtest

Permutational paired t-test

tpaired.krandtest

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

Function to compute a scalogram

Function to compute and test eigenvectors of spatial weighting matrices

Function to compute multivariate empirical variogram

Space-time interaction in ANOVA without replication