Ebook: Multivariate Methods of Representing Relations in R for Prioritization Purposes: Selective Scaling, Comparative Clustering, Collective Criteria and Sequenced Sets
- Tags: Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences, Statistics for Life Sciences Medicine Health Sciences
- Series: Environmental and Ecological Statistics 6
- Year: 2012
- Publisher: Springer-Verlag New York
- Edition: 1
- Language: English
- pdf
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.
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. The intention is to provide an extensive entry into the realms of R using exploration by example whereby a demonstrative dataset of manageably moderate size is carried comparatively though the sequence of sections.
· Third is a major mission to introduce innovative methodologies for preliminary and/or partial prioritization that arise from partial order theory. We formulate functions in R that provide for generation and visualization of partial orderings based on combinations of criteria. These methods support etiological exploration for explanations that underlie apparent concurrence or conflict among multiple indicators of suitability or severity.
Fourth is delving more deeply into some multivariate methods such as principal components using the matrix methods available in R. R makes highly compact calls available for several such multivariate methods, but sometimes discernment demands delving into details.
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. The intention is to provide an extensive entry into the realms of R using exploration by example whereby a demonstrative dataset of manageably moderate size is carried comparatively though the sequence of sections.
· Third is a major mission to introduce innovative methodologies for preliminary and/or partial prioritization that arise from partial order theory. We formulate functions in R that provide for generation and visualization of partial orderings based on combinations of criteria. These methods support etiological exploration for explanations that underlie apparent concurrence or conflict among multiple indicators of suitability or severity.
Fourth is delving more deeply into some multivariate methods such as principal components using the matrix methods available in R. R makes highly compact calls available for several such multivariate methods, but sometimes discernment demands delving into details.
Content:
Front Matter....Pages i-xviii
Front Matter....Pages 11-11
Motivation and Computation....Pages 1-10
Front Matter....Pages 11-11
Suites of Scalings....Pages 13-30
Rotational Rescaling and Disposable Dimensions....Pages 31-42
Comparative Clustering for Contingent Collectives....Pages 43-62
Distance Domains, Skeletal Structures, and Representative Ranks....Pages 63-90
Front Matter....Pages 91-91
Ascribed Advantage, Subordination Schematic, and ORDIT Ordering....Pages 93-100
Precedence Plots, Coordinated Criteria, and Rank Relations....Pages 101-115
Case Comparisons and Precedence Pools....Pages 117-152
Distal Data and Indicator Interactions....Pages 153-163
Landscape Linkage for Prioritizing Proximate Patches....Pages 165-180
Constellations of Criteria....Pages 181-192
Severity Setting for Human Health....Pages 193-205
Front Matter....Pages 207-207
Matrix Methods for Multiple Measures....Pages 209-229
Segregating Sets Along Directions of Discrimination....Pages 231-243
Back Matter....Pages 245-297
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. The intention is to provide an extensive entry into the realms of R using exploration by example whereby a demonstrative dataset of manageably moderate size is carried comparatively though the sequence of sections.
· Third is a major mission to introduce innovative methodologies for preliminary and/or partial prioritization that arise from partial order theory. We formulate functions in R that provide for generation and visualization of partial orderings based on combinations of criteria. These methods support etiological exploration for explanations that underlie apparent concurrence or conflict among multiple indicators of suitability or severity.
Fourth is delving more deeply into some multivariate methods such as principal components using the matrix methods available in R. R makes highly compact calls available for several such multivariate methods, but sometimes discernment demands delving into details.
Content:
Front Matter....Pages i-xviii
Front Matter....Pages 11-11
Motivation and Computation....Pages 1-10
Front Matter....Pages 11-11
Suites of Scalings....Pages 13-30
Rotational Rescaling and Disposable Dimensions....Pages 31-42
Comparative Clustering for Contingent Collectives....Pages 43-62
Distance Domains, Skeletal Structures, and Representative Ranks....Pages 63-90
Front Matter....Pages 91-91
Ascribed Advantage, Subordination Schematic, and ORDIT Ordering....Pages 93-100
Precedence Plots, Coordinated Criteria, and Rank Relations....Pages 101-115
Case Comparisons and Precedence Pools....Pages 117-152
Distal Data and Indicator Interactions....Pages 153-163
Landscape Linkage for Prioritizing Proximate Patches....Pages 165-180
Constellations of Criteria....Pages 181-192
Severity Setting for Human Health....Pages 193-205
Front Matter....Pages 207-207
Matrix Methods for Multiple Measures....Pages 209-229
Segregating Sets Along Directions of Discrimination....Pages 231-243
Back Matter....Pages 245-297
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