nmds {labdsv} | R Documentation |
This function is simply a wrapper for the isoMDS function in the MASS package by Venables and Ripley. The purpose is to establish a nmds class to simplify plotting and additional graphical analysis as well as a summary.
nmds(dis,k=2,y=cmdscale(d=dis,k=k),maxit=50) bestnmds(dis,k=2,itr=20,maxit=100)
dis |
a dist object returned from dist() or a full symmetric
dissimilarity or distance matrix |
k |
the desired number of dimensions for the result |
y |
a matrix of initial locations (objects as rows, coordinates as columns,
as many columns as specified by k). If none is supplied, cmdscale
is used to generate them |
maxit |
the maximum number of iterations |
itr |
number of random starts to find best result |
The nmds function simply calls the isoMDS()
function of the
MASS library, but converts the result from a list to an object of
class "nmds." The only purpose for the function is to allow ‘plot’,
‘identify’,
‘surf’, and other additional methods to be defined for the
nmds class, to simplify the analysis of the result.
The ‘bestnmds’ function runs ‘itr’ number of random initial locations and returns the best result of the set.
an object of class ‘nmds’, with components:
points |
the coordinates of samples along axes |
stress |
the "goodness-of-fit" computed as stress in percent |
nmds is included as part of the LabDSV package to provide a consistent interface and utility for vegetation ordination methods. Other analyses included with the same interface include principal components analysis (pca), principal coordinates analysis (pco), correspondence analysis (ca), canonical correspondence analysis (cca), and fuzzy set ordination (fso).
Venables and Ripley for the original isoMDS function
David W. Roberts droberts@montana.edu http://ecology.msu.montana.edu/labdsv for the nmds class and interface
Kruskal, J.B. (1964) Multidimensional scaling by optimizing goodness of fit to nonmetric hypothesis. Psychometrics 29:1-27.
Kruskal, J.B. (1964) Nonmetric multidimensional scaling: a numerical method. Psychometrics 29:115-129.
T.F. Cox and M.A.A. Cox. (1994) Multidimensional Scaling. Chapman and Hall.
isoMDS
for the original function
plot.nmds
for the plot method
points.nmds
for a points method
plotid.nmds
for a function to identify points in the graphic
surf.nmds
for a function to plot contours of independent variables
on top of the graphic (using the gam
and interp
functions
to calculate the surface
jsurf.nmds
for a function to plot contours of independent variables
on top of the graphic (using the gam()
and interp()
functions
to calculate the surface. Jitters the coordinates of points on the axes
to avoid errors in the embedded interp
function.
bestnmds
for a way to automate multiple ramdom starts and save the
best result
initMDS
for an alternative way to automate random starts
postMDS
for a post-solution rescaling
metaMDS
for a full treatment of variations
data(bryceveg) data(brycesite) dis.man <- dist(bryceveg,method="manhattan") demo.nmds <- nmds(dis.man,k=4) plot(demo.nmds) data(brycesit) points(demo.nmds,brycesite$elev>8000) plotid(demo.nmds)