eigenmap-class | R Documentation |
Create and handle spatial eigenvector maps of a set of locations a space with an arbitrary number of dimensions.
## S3 method for class 'eigenmap'
print(x, ...)
## S3 method for class 'eigenmap'
plot(x, ...)
x |
an 'eigenmap-class' object. |
... |
Further parameters to be passed to other functions or methods (currently ignored). |
'eigenmap-class' objects contain:
A matrix of coordinates.
The interval within which pairs of sites are considered as neighbours.
A distance matrix.
The weighting function that had been used.
The weighting function parameter that had been used.
A vector of the eigenvalues obtain from the computation of the eigenvector map.
A matrix of the eigenvectors defining the eigenvector map.
The 'print' method provides the number of the number of orthonormal variables (i.e. basis functions), the number of observations these functions are spanning, and their associated eigenvalues.
The 'plot' method provides a plot of the eigenvalues and offers the
possibility to plot the values of variables for 1- or 2-dimensional sets of
coordinates. plot.eigenmap
opens the default graphical device driver,
i.e., X11
, windows
, or quartz
and recurses through
variable with a left mouse click on the graphical window. A right mouse click
interrupts recursing on X11
and windows
(Mac OS X users should
hit Esc on the quartz
graphical device driver (Mac OS X users).
print(eigenmap)
: Print method for eigenmap-class objects
plot(eigenmap)
: Plot method for eigenmap-class objects
Guillaume Guenard and Pierre Legendre, Bertrand Pages Maintainer: Guillaume Guenard <guillaume.guenard@gmail.com>
Borcard, D. and Legendre, P. 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model. 153: 51-68
Dray, S.; Legendre, P. and Peres-Neto, P. 2006. Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbor matrices (PCNM). Ecol. Modelling 196: 483-493
Legendre, P. and Legendre, L. 2012. Numerical Ecology, 3rd English edition. Elsevier Science B.V., Amsterdam, The Netherlands.
MCA
eigenmap
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