Nonmetric Multidimensional Scaling
This function is simply a wrapper for the isoMDS function in the MASS package by Venables and Ripley. The purpose is to convert the output to class ‘dsvord’ to simplify plotting and additional graphical analysis as well as to provide a summary method.
nmds(dis,k=2,y=cmdscale(d=dis,k=k),maxit=50,trace=FALSE) bestnmds(dis,k=2,itr=20,maxit=100,trace=FALSE)
dis |
a dist object returned from |
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, |
maxit |
the maximum number of iterations in the isoMDS routine |
trace |
a switch to control printing intermediate results |
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 ‘dsvord’. The only purpose for the function is to allow ‘plot’,
‘identify’,
‘surf’, and other additional methods to be defined for the
class, to simplify the analysis of the result.
The ‘bestnmds’ function runs one run from a PCO solution and ‘itr-1’ number of random initial locations and returns the best result of the set.
An object of class ‘dsvord’, with components:
points |
the coordinates of samples along axes |
stress |
the "goodness-of-fit" computed as stress in percent |
type |
‘NMDS’ |
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 at present include principal components analysis (pca), principal coordinates analysis (pco), and t-distributed neighborhood embedding (t-SNE).
Venables and Ripley for the original isoMDS function included in the MASS package.
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.dsvord for the ‘plot’ method, the ‘plotid’
method to identify points with a mouse, the ‘points’ method to
identify points meeting a logical condition, the ‘hilight’ method
to color-code points according to a factor,
the ‘chullord’ method to add convex hulls for a factor, or the
the ‘surf’ method to add surface contours for
continuous variables.
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) points(demo.nmds,brycesite$elev>8000) plotid(demo.nmds,ids=row.names(brycesite))
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