The book starts with a range of examples and develops techniques progressively, starting with standard least squares prediction of a single variable from another and moving onto shrinkage techniques for multiple variables. Chapters 6 and 7 refer mostly to methods that have been specifically developed for spectroscopy. The other chapters are quite general in their applicability. Likelihood and Bayesian inference features strongly, the latter allowing flexible analysis of a wide range of multivariate regression problems. The last chapter presents some Bayesian approaches to pattern recognition.
For teaching purposes instructors may find particular chapters sufficiently self contained to recommend in isolation as reference or reading material. For example chapter 4 gives an in depth development of a range of shrinkage techniques. including partial least squares regression, ridge regression and principal components regression; together with discussion of the recently proposed continuum regression. Chapter 8 on pattern recognition may also be of us by itself in courses on multivariate analysis and Bayesian Statistics.
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Charlotte y Peter Fiell son dos autoridades en historia, teoría y crítica del diseño y han escrito más de sesenta libros sobre la materia, muchos de los cuales se han convertido en éxitos de ventas. También han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Diseño del siglo XX, El diseño industrial de la A a la Z, Scandinavian Design y Diseño del siglo XXI.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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Hardcover. Zustand: new. Hardcover. The book starts with a range of examples and develops techniques progressively, starting with standard least squares prediction of a single variable from another and moving onto shrinkage techniques for multiple variables. Chapters 6 and 7 refer mostly to methods that have been specifically developed for spectroscopy. The other chapters are quite general in their applicability. Likelihood and Bayesian inference features strongly, the latter allowing flexibleanalysis of a wide range of multivariate regression problems. The last chapter presents some Bayesian approaches to pattern recognition.For teaching purposes instructors may findparticular chapters sufficiently self contained to recommend in isolation as reference or reading material. For example chapter 4 gives an in depth development of a range of shrinkage techniques. including partial least squares regression, ridge regression and principal components regression; together with discussion of the recently proposed continuum regression. Chapter 8 on pattern recognition may also be of us by itself in courses on multivariate analysis and Bayesian Statistics. This book explains the statistical theory behind a range of regression problems in which one set of variables is predicted from another. The applications are from industry and medicine where the researchers are using sophisticated electronic measuring devices that are capable of monitoring very many variables. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9780198522454
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