This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number ofexercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Nickolay T. Trendafilov is Reader of Computational Statistics in the School of Mathematics and Statistics, Open University, UK. He received MSc and PhD in the Department of Mathematics and Informatics, University of Sofia “St. Kl. Ohridski”, and then joined the Laboratory of Computational Stochastic, Bulgarian Academy of Sciences. He held research and visiting positions in a number of universities in Belgium, Italy, Japan and USA. His interests are in the computational aspects of multivariate data analysis and interpretation. Other activities include elected memberships in the International Statistical Institute (ISI), the Royal Statistical Society's (RSS) Computing Section, and the Board of Directors, European Regional Section of the International Association for Statistical Computing (IASC).
Michele Gallo is Professor in the Department of Human and Social Sciences at the University of Naples – L’Orientale. He received his PhD degree in Total Quality Management from the University of Naples – Federico II, in 2000. His current research interest is in Multivariate Data Analysis, Compositional and Ordinal Data, Rasch Analysis. He has published more than 90 research articles. He is Associate-Editor of the journal Computational Statistics.
This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number ofexercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 17,24 für den Versand von USA nach Deutschland
Versandziele, Kosten & DauerGratis für den Versand innerhalb von/der Deutschland
Versandziele, Kosten & DauerAnbieter: moluna, Greven, Deutschland
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt.This graduate-level textbook aims to give a unified p. Bestandsnummer des Verkäufers 467591450
Anzahl: Mehr als 20 verfügbar
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Bestandsnummer des Verkäufers ABNR-11925
Anzahl: 2 verfügbar
Anbieter: Basi6 International, Irving, TX, USA
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verkäufers ABEJUNE24-260425
Anzahl: 7 verfügbar
Anbieter: Speedyhen, London, Vereinigtes Königreich
Zustand: NEW. Bestandsnummer des Verkäufers NW9783030769734
Anzahl: 1 verfügbar
Anbieter: Basi6 International, Irving, TX, USA
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verkäufers ABEJUNE24-260426
Anzahl: 1 verfügbar
Anbieter: SMASS Sellers, IRVING, TX, USA
Zustand: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed. Bestandsnummer des Verkäufers ASNT3-11925
Anzahl: 2 verfügbar
Anbieter: Basi6 International, Irving, TX, USA
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Bestandsnummer des Verkäufers ABEJUNE24-13772
Anzahl: 1 verfügbar
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Bestandsnummer des Verkäufers GB-9783030769734
Anzahl: 1 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: Neu. Neuware -This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number ofexercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 472 pp. Englisch. Bestandsnummer des Verkäufers 9783030769734
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number ofexercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization. Bestandsnummer des Verkäufers 9783030769734
Anzahl: 2 verfügbar