Isbn: 9783330853522 - semi-definite programming as a model for statistical data analysis (6 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Noor Publishing, 2017

    3330853522 / 9783330853522

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    Paperback. Zustand: Brand New. 60 pages. 8.66x5.91x0.14 inches. In Stock.

  • Sprache: Englisch

    Verlag: Noor Publishing, 2017

    3330853522 / 9783330853522

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    Taschenbuch. Zustand: Neu. Semi-Definite Programming as a Model for Statistical Data Analysis | Abdul-Hameed Al-Ibrahim | Taschenbuch | 60 S. | Englisch | 2017 | Noor Publishing | EAN 9783330853522 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: Noor Publishing Mrz 2017, 2017

    3330853522 / 9783330853522

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    Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this monograph I present a method to derive a minimum rank covariance matrix for several continuous variables. The minimum rank problem appears in many areas of multivariate analysis as well as in many applications of multivariate analysis such as in biology, medicine, psychology, pharmacology, and machine learning. The method seems to be extremely powerful and enjoys many optimal properties. It is a non-linear distribution-free method that encompases under its umberla major topics such as Factor Analysis, Principal Componens Analysis, MDS, and Multiple Regression. The monograph is composed of two papers, the first of which sets the foundations and the theoratical basis for developing the underlying theory. It also presents several applications of the method. As for the second paper, it includes several examples of a completely different type of applications of the method. In these applications values of interactions are derived from only binary data such as low and high levels of interaction among pairs of objects. The key in all these applications is the low rank property of the covariance matrix which is the criterion for optimality of the method. 60 pp. Englisch.

  • Sprache: Englisch

    Verlag: Noor Publishing, 2017

    3330853522 / 9783330853522

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    Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Al-Ibrahim Abdul-Hameed- Ph.D in Statistics from University of Wyoming, USA, 1986- Assistant Professor of Statistics in Kuwait University, Kuwait- Associate Professor of Statistics, American University of the Middle East- Statistical.

  • Sprache: Englisch

    Verlag: Noor Publishing Mär 2017, 2017

    3330853522 / 9783330853522

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    Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this monograph I present a method to derive a minimum rank covariance matrix for several continuous variables. The minimum rank problem appears in many areas of multivariate analysis as well as in many applications of multivariate analysis such as in biology, medicine, psychology, pharmacology, and machine learning. The method seems to be extremely powerful and enjoys many optimal properties. It is a non-linear distribution-free method that encompases under its umberla major topics such as Factor Analysis, Principal Componens Analysis, MDS, and Multiple Regression. The monograph is composed of two papers, the first of which sets the foundations and the theoratical basis for developing the underlying theory. It also presents several applications of the method. As for the second paper, it includes several examples of a completely different type of applications of the method. In these applications values of interactions are derived from only binary data such as low and high levels of interaction among pairs of objects. The key in all these applications is the low rank property of the covariance matrix which is the criterion for optimality of the method.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch.

  • Sprache: Englisch

    Verlag: Noor Publishing, 2017

    3330853522 / 9783330853522

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    Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this monograph I present a method to derive a minimum rank covariance matrix for several continuous variables. The minimum rank problem appears in many areas of multivariate analysis as well as in many applications of multivariate analysis such as in biology, medicine, psychology, pharmacology, and machine learning. The method seems to be extremely powerful and enjoys many optimal properties. It is a non-linear distribution-free method that encompases under its umberla major topics such as Factor Analysis, Principal Componens Analysis, MDS, and Multiple Regression. The monograph is composed of two papers, the first of which sets the foundations and the theoratical basis for developing the underlying theory. It also presents several applications of the method. As for the second paper, it includes several examples of a completely different type of applications of the method. In these applications values of interactions are derived from only binary data such as low and high levels of interaction among pairs of objects. The key in all these applications is the low rank property of the covariance matrix which is the criterion for optimality of the method.