R/rpowerStressMin.R

In cops: Cluster Optimized Proximity Scaling

## #' Restricted Power Stress SMACOF
## #'
## #' An implementation to minimize restricted power stress by majorization with ratio or interval optimal scaling. Restricted means that the same power is used for both dissimilarities and fitted distances. Usually more accurate but slower than powerStressFast. Uses a repeat loop.
## #' 
## #' @param delta dist object or a symmetric, numeric data.frame or matrix of distances
## #' @param expo power of the transformation of the fitted distances and dissimilarities; defaults to 1
## #' @param nu the power of the transformation for weightmat; defaults to 1
## #' @param type what type of MDS to fit. One of "ratio" or "interval". Default is "ratio".
## #' @param weightmat a matrix of finite weights
## #' @param init starting configuration
## #' @param ndim dimension of the configuration; defaults to 2
## #' @param acc numeric accuracy of the iteration. Default is 1e-6.
## #' @param itmax maximum number of iterations. Default is 10000.
## #' @param verbose should iteration output be printed; if > 1 then yes
## #' @param principal If ‘TRUE’, principal axis transformation is applied to the final configuration
## #'
## #' @return a smacofP object (inheriting form smacofB, see \code{\link{smacofSym}}). It is a list with the components
## #' \itemize{
## #' \item delta: Observed, untransformed dissimilarities
## #' \item tdelta: Observed explicitly transformed dissimilarities, normalized
## #' \item dhat: Explicitly transformed dissimilarities (dhats), optimally scaled and normalized 
## #' \item confdist: Configuration dissimilarities
## #' \item conf: Matrix of fitted configuration
## #' \item stress: Default stress  (stress 1; sqrt of explicitly normalized stress)
## #' \item spp: Stress per point 
## #' \item ndim: Number of dimensions
## #' \item model: Name of smacof model
## #' \item niter: Number of iterations
## #' \item nobj: Number of objects
## #' \item type: Type of MDS model 
## #' \item weightmat: weighting matrix as supplied 
## #' \item stress.m: Default stress (stress-1^2)
## #' \item tweightmat: transformed weighthing matrix (here weightmat^nu)
## #' \item parameters, pars, theta: The parameter vector of the explicit transformations
## #' }
## #'
## #' 
## #' 
## #' @examples
## #' dis<-smacof::kinshipdelta
## #' res<-rpowerStressMin(as.matrix(dis),expo=1.7,itmax=1000)
## #' res
## #' summary(res)
## #' plot(res)
## #' 
## #' @export
## rpowerStressMin <- function (delta, expo=1, nu=1,  type="ratio", weightmat=1-diag(nrow(delta)), init=NULL, ndim = 2, acc= 1e-6, itmax = 10000, verbose = FALSE, principal=FALSE) {
##     out <- powerStressMin(delta=delta, kappa=expo, lambda=expo, nu=nu,  type=type, weightmat=weightmat, init=init, ndim = ndim, acc= acc, itmax = itmax, verbose = verbose, principal=principal)
##     return(out)
## }

## #' @rdname rpowerStressMin
## #' @export
## rpowerstressMin <- rpowerStressMin

## #' @rdname rpowerStressMin
## #' @export
## rpostmds <- rpowerStressMin

## #' @rdname rpowerStressMin
## #' @export
## rpstressMin <- rpowerStressMin

## #' @rdname rpowerStressMin
## #' @export
## rpStressMin <- rpowerStressMin

## #' @rdname rpowerStressMin
## #' @export
## rpstressmds <- rpowerStressMin