Structure Optimized Proximity Scaling
c-inequality Calculates c-inequality (as in an economic measure of ine...
c-linearity calculates c-linearity as the aggregated multiple correlat...
c-sparsity
c-striatedness
c-stringiness
S3 coef method for stops objects
STOPS version of Box Cox Stress
MDS Bootstrap for stops objects
c-association calculates the c-association based on the maximal inform...
c-clumpiness
c-clusteredness calculates c-clusteredness as the OPTICS cordillera. T...
c-complexity Calculates the c-complexity based on the minimum cell num...
c-convexity
c-dependence calculates c-dependence as the aggregated distance correl...
c-faithfulness calculates the c-faithfulness based on the index by Che...
c-functionality calculates the c-functionality based on the maximum ed...
c-hierarchy captures how well a partition/ultrametric (obtained by hcl...
c-manifoldness calculates c-manifoldness as the aggregated maximal cor...
wrapper for getting the mine coefficients
c-nonmonotonicity calculates the c-nonmonotonicity based on the maximu...
c-outlying
c-regularity calculates c-regularity as 1 - OPTICS cordillera for k=2....
c-shepardness calculates the c-shepardness as the correlation between ...
c-skinniness
MDS Jackknife for stops objects
calculate k nearest neighbours from a distance matrix
(Adaptive) Version of Luus-Jaakola Optimization
S3 plot method for stops objects
S3 print method for stops objects
S3 print method for summary.stops
S3 residuals method for stops
STOPS version of approximated power stress models.
STOPS version of CLCA.
STOPS version of CLDA with free epsilon.
STOPS version of CLDA with free k.
STOPS version of strain
STOPS version of elastic scaling with powers for proximities and dista...
STOPS versions of elastic scaling models (via smacofSym)
STOPS version of isomap to optimize over integer k.
STOPS version of isomap over real epsilon.
STOPS version of lMDS
STOPS version of powermds
STOPS version of sammon with powers
STOPS version of powerstress
STOPS version of restricted powerstress
STOPS version of rstress
STOPS version of Sammon mapping
Another STOPS version of Sammon mapping models (via smacofSym)
STOPS versions of smacofSphere models
STOPS version of smacofSym models
STOPS version of sparsified multidimensional distance analysis for fix...
STOPS version of sparsified multidimensional distance analysis for fix...
STOPS version of sparsified MDS.
STOPS version of sparsified post multidimensional distance analysis fo...
STOPS version of sparsified post multidimensional distance analysis fo...
STOPS version of sparsified POST-MDS for fixed tau
STOPS version of sstress
Calculate the weighted multiobjective loss function used in STOPS
stops: Structure Optimized Proximity Scaling
High Level STOPS Function
S3 summary method for stops
Bayesian Optimization by a (treed) Bayesian Gaussian Process Prior (wi...
Methods that use flexible variants of multidimensional scaling (MDS) which incorporate parametric nonlinear distance transformations and trade-off the goodness-of-fit fit with structure considerations to find optimal hyperparameters, also known as structure optimized proximity scaling (STOPS) (Rusch, Mair & Hornik, 2023,<doi:10.1007/s11222-022-10197-w>). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying different 1-way MDS models with ratio, interval, ordinal optimal scaling in a STOPS framework. These cover essentially the functionality of the package smacofx, including Torgerson (classical) scaling with power transformations of dissimilarities, SMACOF MDS with powers of dissimilarities, Sammon mapping with powers of dissimilarities, elastic scaling with powers of dissimilarities, spherical SMACOF with powers of dissimilarities, (ALSCAL) s-stress MDS with powers of dissimilarities, r-stress MDS, MDS with powers of dissimilarities and configuration distances, elastic scaling powers of dissimilarities and configuration distances, Sammon mapping powers of dissimilarities and configuration distances, power stress MDS (POST-MDS), approximate power stress, Box-Cox MDS, local MDS, Isomap, curvilinear component analysis (CLCA), curvilinear distance analysis (CLDA) and sparsified (power) multidimensional scaling and (power) multidimensional distance analysis (experimental models from smacofx influenced by CLCA). All of these models can also be fit by optimizing over hyperparameters based on goodness-of-fit fit only (i.e., no structure considerations). The package further contains functions for optimization, specifically the adaptive Luus-Jaakola algorithm and a wrapper for Bayesian optimization with treed Gaussian process with jumps to linear models, and functions for various c-structuredness indices.