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Selective Scaling, Comparative Clustering, Collective Criteria and Sequenced Sets
Supporting the assertion that multiple views of data have a greater prospect of revealing prominent patterns than single views, this book provides a portal into the open source data analysis system called R though exposition by example.
This monograph is multivariate, multi-perspective and multipurpose. We intend to be innovatively integrative through statistical synthesis. Innovation requires capacity to operate in ways that are not ordinary, which means that conventional computations and generic graphics will not meet the needs of an adaptive approach. Flexible formulation and special schematics are essential elements that must be manageable and economical.
Motivation and Computation.- Part I: Synergistic Scalings, Contingent Clustering and Distance Domains.- Suites of Scalings.- Rotational Rescaling and Disposable Dimensions.- Comparative Clustering for Contingent Collectives.- Distance Domains, Skeletal Structures and Representative Ranks.- Part II: Precedence and Progressive Prioritization.- Ascribed Advantage, Subordination Schematic and ORDIT Ordering.- Precedence Plots, Coordinated Crite4ria and Rank Relations.- Case Comparisons and Precedence Pools.- Distal Data and Indicator Interactions.- Landscape Linkage for Prioritizing Proximate Patches.- Constellations of Criteria.- Severity Setting for Human Health.- Part III: Transformation Techniques and Virtual Variates.- Matrix Methods for Multiple Measures.- Segregating Sets Along Directions of Discrimination.- Index.