Isbn: 9789811001574 - nonlinear principal component analysis and its applications (jss research series in statistics) (4 Ergebnisse)

- Softcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 78,93
EUR 10,93 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In English.

- Softcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 91,00
EUR 11,67 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
Paperback. Zustand: Brand New. 88 pages. 9.00x6.00x0.25 inches. In Stock.

- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 72,32
EUR 35,00 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed measurement levels data, sparse MCA, joint dimension reduction and clustering methods for categorical data, and acceleration of ALS computation. The variable selection methods in PCA that originally were developed for numerical data can be applied to any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the results of recent studies, are extensions obtained by the same matrix operations in nonlinear PCA. Finally, an acceleration algorithm is proposed to reduce the problem of computational cost in the ALS iteration in nonlinear multivariate methods. This book thus presents the usefulness of nonlinear PCA which can be applied to different measurement levels data in diverse fields. As well, it covers the latest topics including the extension of the traditional statistical method, newly proposed nonlinear methods, and computational efficiency in the methods.…
Weitere Bilder- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 59,40
EUR 70,00 VersandVersand von Deutschland nach USAAnzahl: 5 verfügbar
Taschenbuch. Zustand: Neu. Nonlinear Principal Component Analysis and Its Applications | Yuichi Mori (u. a.) | Taschenbuch | x | Englisch | 2016 | Springer Nature Singapore | EAN 9789811001574 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …