Synopses & Reviews
This monograph is a four-fold featuring of adaptive analysis. · First is data distillation and comparative coupling whereby the results of one analysis are fed forward into another analysis without necessarily returning directly to the original data matrix and analytical avenues usually seen as alternatives are pursued in parallel with results being carried forward together as complementary comparatives. · Second is the flexibility and suitability of the R© statistical software system for engaging in such adaptive and conjunctive statistical strategies.
Synopsis
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."
Synopsis
This monograph is multivariate, multi-perspective and multipurpose.
Synopsis
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.
Table of Contents
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.