smacofx (version 1.6-1)

clda: Curvilinear Distance Analysis (CLDA)

Description

A function to run curvilinear distance analysis via CCA and returning a 'smacofP' object. Note this functionality is rather rudimentary.

Usage

clda(
  delta,
  Epochs = 20,
  alpha0 = 0.5,
  lambda0,
  ndim = 2,
  weightmat = 1 - diag(nrow(delta)),
  init = NULL,
  acc = 1e-06,
  itmax = 10000,
  verbose = 0,
  method = "euclidean",
  principal = FALSE,
  epsilon,
  k,
  path = "shortest",
  fragmentedOK = FALSE
)

Value

a 'smacofP' object. It is a list with the components

• delta: Observed, untransformed dissimilarities

• tdelta: Observed explicitly transformed dissimilarities, normalized

• dhat: Explicitly transformed dissimilarities (dhats), optimally scaled and normalized

• confdist: Configuration dissimilarities

• conf: Matrix of fitted configuration

• stress: Default stress (stress-1; sqrt of explicitly normalized stress)

• spp: Stress per point

• ndim: Number of dimensions

• model: Name of model

• niter: Number of iterations (training length)

• nobj: Number of objects

• type: Type of MDS model. Only ratio here.

• weightmat: weighting matrix as supplied

• stress.m: Default stress (stress-1^2)

• tweightmat: transformed weighting matrix; it is weightmat here.

Arguments

delta

dist object or a symmetric, numeric data.frame or matrix of distances. Will be turne dinto geodesci distances.

Epochs

Scalar; gives the number of passes through the data.

alpha0

(scalar) initial step size, 0.5 by default

lambda0

the boundary/neighbourhood parameter(s) (called lambda_y in the original paper). It is supposed to be a numeric scalar. It defaults to the 90% quantile of delta.

ndim

dimension of the configuration; defaults to 2

weightmat

not used

init

starting configuration, not used

acc

numeric accuracy of the iteration; not used

itmax

maximum number of iterations. Not used.

verbose

should iteration output be printed; not used

method

Distance calculation; currently not used.

principal

If 'TRUE', principal axis transformation is applied to the final configuration

epsilon

Shortest dissimilarity retained.

k

Number of shortest dissimilarities retained for a point. If both 'epsilon' and 'k' are given, 'epsilon' will be used.

path

Method used in 'stepacross' to estimate the shortest path, with alternatives '"shortest"' and '"extended"'.

fragmentedOK

What to do if dissimilarity matrix is fragmented. If 'TRUE', analyse the largest connected group, otherwise stop with error.

Details

This implements CLDA as CLCA with geodesic distances. The geodesic distances are calculated via 'vegan::isomapdist', see isomapdist for a documentation of what these distances do. 'clda' is just a wrapper for 'clca' applied to the geodesic distances obtained via isomapdist.

Examples

dis<-smacof::morse
res<-clda(dis,lambda0=0.4,k=4)
res
summary(res)
plot(res)