Structure optimized proximity scaling (STOPS) refers to 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, COPS-0, COPS-C and P-COPS. All of these models can also solely be fit as MDS with power transformations. 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.
|Author||Thomas Rusch [aut, cre], Jan de Leeuw [aut], Patrick Mair [aut], Kurt Hornik [ctb]|
|Date of publication||2016-11-30 16:32:06|
|Maintainer||Thomas Rusch <firstname.lastname@example.org>|
|License||GPL-2 | GPL-3|
|Package repository||View on R-Forge|
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