stops {stops}R Documentation

stops: structure optimized proximity scaling

Description

A package for "structure optimized proximity scaling" (STOPS), a collection of methods that fit nonlinear distance transformations in multidimensional scaling (MDS) and trade-off the fit with structure considerations to find optimal parameters or optimal configurations. This includes the three variants of cluster optimized proximity scaling (COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different MDS models in a STOPS framework like Torgerson scaling, SMACOF, Sammon mapping, elastic scaling, symmetric SMACOF, spherical SMACOF, sstress, rstress, powermds, power elastic scaling, power sammon mapping, powerstress, isomap. All of these models can also be fit as MDS variants (i.e., no structuredness). The package further contains functions for optimization (Adaptive LJ and for Bayesian optimization with treed Gaussian process with jump to linear models) and functions for various structuredness indices

High Level STOPS Function

Usage

stops(dis, loss = c("strain", "stress", "smacofSym", "powerstress",
  "powermds", "powerelastic", "powerstrain", "elastic", "sammon", "sammon2",
  "smacofSphere", "powersammon", "rstress", "sstress", "isomap", "isomapeps"),
  theta = 1, structures = c("cclusteredness", "clinearity", "cdependence",
  "cmanifoldness", "cassociation", "cnonmonotonicity", "cfunctionality",
  "ccomplexity", "cfaithfulness", "cregularity"), ndim = 2,
  weightmat = NULL, init = NULL, stressweight = 1, strucweight, strucpars,
  optimmethod = c("SANN", "ALJ", "pso", "Kriging", "tgp"), lower = c(1, 1,
  0.5), upper = c(5, 5, 2), verbose = 0, type = c("additive",
  "multiplicative"), s = 5, initpoints = 10, itmax = 50, model, ...)

Arguments

dis

numeric matrix or dist object of a matrix of proximities

loss

which loss function to be used for fitting, defaults to stress

theta

parameters for the proximiy and distance transformation

structures

what c-structuredness should be considered; if missing no structure is considered.

ndim

number of dimensions of the target space

weightmat

(optional) a matrix of nonnegative weights; defaults to 1 for all off diagonals

init

(optional) initial configuration

stressweight

weight to be used for the fit measure; defaults to 1

strucweight

weight to be used for the cordillera; defaults to -1/length(structures)

strucpars

list of parameters for the structuredness indices; must be in the same ordering as the indices in structures. If missing it is set to NULL.

optimmethod

What optimizer to use? Currently supported are Bayesian optimization with Gaussian Process priors and Kriging ("Kriging"), Bayesian optimization with treed Gaussian processes ("tgp"), Adaptive LJ Search ("ALJ"), Particle Swarm optimization ("pso"), simulated annealing ("SANN"). Defaults to ALJ version.

lower

The lower contraints of the search region

upper

The upper contraints of the search region

verbose

numeric value hat prints information on the fitting process; >2 is very verbose

type

which aggregation for the multi objective target function? Either 'additive' (default) or 'multiplicative'

s

number of particles if pso is used

initpoints

number of initial points to fit the surrogate model for bayesian optimization; default is 10

itmax

maximum number of iterations; number of steps of Bayesian optimization if Kriging or tgp is used; default is 50. Note that with tgp the actual number of evaluation of the MDS method is between itmax and 5*itmax as tgp it samples 1-5 candidates from the posterior and uses the best candidate.

model

a character specifying the surrogate model to use. For Kriging it specifies the covariance kernel for the GP prior; see covTensorProduct-class defaults to "powerexp". For tgp it specifies the non stationary process used see bgp, defaults to "btgpllm"

...

additional arguments to be passed to the optimization procedure

Details

The stops package provides five categories of important functions:

Models & Algorithms:

Structuredness Indices:

Optimization functions:

Wrappers and convenience functions:

Methods: For most of the objects returned by the high-level functions S3 classes and methods for standard generics were implemented, including print, summary, plot, plot3d, plot3dstatic.

References:

Authors: Thomas Rusch, Jan de Leeuw, Patrick Mair

Maintainer: Thomas Rusch

Value

A list with the components

Examples

library(cordillera)
data(BankingCrisesDistances)


#STOPS
strucpars<-list(c(epsilon=10,minpts=2),NULL)
res<-stops(BankingCrisesDistances[,1:69],loss="strain",
structures=c("cclusteredness","clinearity"),strucpars=strucpars,optimmethod="Kriging")
res
summary(res)
plot(res)
plot(res,"Shepard")


data(BankingCrisesDistances)
strucpar<-list(c(eps=10,minpts=2),NULL)
res1<-stops(BankingCrisesDistances[,1:69],loss="stress",verbose=0,
structures=c("cclusteredness","clinearity"),
strucpars=strucpar)
res1

strucpar<-list(list(alpha=1,C=15,var.thr=1e-5,eps=NULL),list(alpha=1,C=15,var.thr=1e-5,eps=NULL))
res1<-stops(BankingCrisesDistances[,1:69],loss="stress",verbose=0,
structures=c("cfunctionality","ccomplexity"),
strucpars=strucpar)
res1



[Package stops version 0.0-40 Index]