Multidimensional Scaling Development Kit
Additive Constant Function for Classical Multidimensional Scaling
Asymmetry Function
Repeated Cross-Validation Penalized Restricted Multidimensional Scalin...
Dilation
Explain method for all fmds objects
Facial Expressions Data
Box-Cox Multidimensional Scaling Function
Stochastic Iterative Majorization Multidimensional Scaling Function
Faster Stress Function
Linear Multidimensional Scaling Function
Multidimensional Scaling Function
Ordinal Multidimensional Scaling Function
Power Multidimensional Scaling Function
Polynomial Multidimensional Scaling Function
Fast Stress Function
Full Multidimensional Scaling Function
Mixed Measurement Level Euclidean Distances Function
Classical Multidimensional Scaling Function
Mark-Recapture Population Size Estimator
Visualisation of an fmds object
Predict method for all fmds objects
Print method for all fmds objects
Relative Density-based Outlier Probabilities Function
Rotation
Summary method for all fmds objects
Multidimensional scaling (MDS) functions for various tasks that are beyond the beta stage and way past the alpha stage. Currently, options are available for weights, restrictions, classical scaling or principal coordinate analysis, transformations (linear, power, Box-Cox, spline, ordinal), outlier mitigation (rdop), out-of-sample estimation (predict), negative dissimilarities, fast and faster executions with low memory footprints, penalized restrictions, cross-validation-based penalty selection, supplementary variable estimation (explain), additive constant estimation, mixed measurement level distance calculation, restricted classical scaling, etc. More will come in the future. References. Busing (2024) "A Simple Population Size Estimator for Local Minima Applied to Multidimensional Scaling". Manuscript submitted for publication. Busing (2025) "Node Localization by Multidimensional Scaling with Iterative Majorization". Manuscript submitted for publication. Busing (2025) "Faster Multidimensional Scaling". Manuscript in preparation. Barroso and Busing (2025) "e-RDOP, Relative Density-Based Outlier Probabilities, Extended to Proximity Mapping". Manuscript submitted for publication.