multistart {smacofx}

Multistart MDS function

Description

For different starting configurations, this function fits a series of PS models given in object or call and returns the one with the lowest stress overall. The starting configuirations can be supplied or are generated internally.

Usage

multistart(
  object,
  mdscall = NULL,
  ndim = 2,
  conflist,
  nstarts = 108,
  return.all = FALSE,
  verbose = TRUE,
  min = -5,
  max = 5
)

Arguments

object

A fitted object of class 'smacofP', 'smacofB' or 'smacof'. If supplied this takes precedence over the call argument. If given this is added to the output and may be the optimal one.

mdscall

Alternatively to a fitted object, one can pass a syntactically valid call for any of the MDS functions cops, stops or smacof that find a configuration (not the ones that do parameter selection like pcops or stops). If object and call is given, object takes precedence.

ndim

Dimensions of target space.

conflist

Optional list of starting configurations.

nstarts

If conflist is not supplied, how many random starting configurations should be used. The default is 108, which implies that at least one of the stress is within the lowest 1 percent of all stresses with probability of 1/3 or within the lowest 5 percent of stresses with probability 0.996

return.all

Should all fitted MDS be returned. If FALSE (default) only the optimal one is returned.

verbose

If >0 prints the fitting progress.

min

lower bound for the uniform distribution to sample from

max

upper bound for the uniform distribution to sample from

Details

If no configuration list is supplied, then nstarts configurations are simulated. They are drawn from a ndim-dimesnional uniform distribution with minimum min and maximum max. We recommend to use the route via supplying a fitted model as these are typically starting from a Torgerson configuration and are likely quite good.

One can simply extract $best and save that and work with it right away.

Value

if 'return.all=FALSE', a list with the best fitted model as '$best' (minimal badness-of-fit of all fitted models) and '$stressvec' the stresses of all models. If 'return.all=TRUE' a list with slots

• best: The object resulting from the fit that had the overall lowest objective function value (usually stress)

• stressvec: The vector of objective function values

• models: A list of all the fitted objects.

Examples

dis<-smacof::kinshipdelta

## Version 1: Using a fitted object (recommended)
res1<-rStressMin(delta=dis,type="ordinal",itmax=100)
resm<-multistart(res1,nstarts=2)
## best model
res2<-resm$best
#it's starting configuration
res2$init

## Version 2: Using a call object and supplying conflist
conflist<-list(res2$init,jitter(res2$init,1))
c1 <- call("rstressMin",delta=dis,type="ordinal",itmax=100)
resm<-multistart(mdscall=c1,conflist=conflist,return.all=TRUE)