Constrained principal component analysis and related techniques /

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In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? W...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Takane, Yoshio (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : CRC Press, [2014]
Colección:Monographs on statistics and applied probability (Series) ; 129.
Temas:
Principal components analysis.
Multivariate analysis.
Multivariate Analysis
Analyse en composantes principales.
Analyse multivariée.
MATHEMATICS > Probability & Statistics > General.
Multivariate analysis
Principal components analysis
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front cover; Contents; List of figures; List of tables; Preface; About the author; Chapter 1: Introduction; Chapter 2: Mathematical foundation; Chapter 3: Constrained principal component analysis (CPCA); Chapter 4: Special cases and related methods; Chapter 5: Related topics of interest; Chapter 6: Different constraints on different dimensions (DCDD); Epilogue; Appendix; Bibliography; Back cover.

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