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adespatial (version 0.3-21)

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

6,905

Version

0.3-21

License

GPL (>= 2)

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Repository

https://github.com/sdray/adespatial

Maintainer

Stéphane Dray

Last Published

March 7th, 2023

Functions in adespatial (0.3-21)

Construct asymmetric eigenvector maps (AEM)

Contingency periodogram

aem.build.binary

Construct a site-by-edge binary matrix

TBI: Difference between multivariate observations at T1 and T2

Compute LCBD from any D matrix

aem.weight.edges

Weight edges when constructing AEM variables

Scotch Whiskey Data Set

Tiahura Transect Fish Data Set

AEM for time series

Whittaker-Robinson periodogram

Dissimilarity matrices for community composition data

Space- And Time-Constrained Clustering

Bacterial production data set

Decompose D in replacement and richness difference components

directional.response

Directional indices of community change

constr.hclust-class

Class For Constrained Hiereachical Clustering

dbMEM spatial eigenfunctions

Beta diversity computed as Var(Y)

create.dbMEM.model

Combine dbMEM matrices corresponding to groups of sites

Function to choose a connection network

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

Mastigouche Lake network data set

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

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

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

Forward selection with multivariate Y using permutation under reducel model

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)

Global and local tests

Moran spectral randomization for fourth-corner analysis

Moran spectral randomization for variation partitioning

msr.mantelrtest

Moran spectral randomization for Mantel test

Function to compute extreme values of Moran's I

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)

Moran spectral randomization

Multi-frequential periodogram analysis

Function to compute Moran's index of spatial autocorrelation

Multi-Scale Pattern Analysis

Compute AIC for models with orthonormal explanatory variables

plot.constr.hclust

Plotting Method For Space- And Time-Constrained Clustering

Plots of the outputs of a temporal beta diversity analysis

orthobasis.poly

Function to compute polynomial of geographical coordinates

Function to compute a scalogram

Space-time interaction in ANOVA without replication

plot.orthobasisSp

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

tpaired.krandtest

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

Rotate a set of point by a certain angle

Function to compute and test eigenvectors of spatial weighting matrices

tpaired.randtest

Permutational paired t-test

Trichoptera data set

Multivariate spatial analysis

Function to compute neighborhood based on the minimum spanning tree

Function to compute multivariate empirical variogram