ISBN: 9783030291631 - advanced linear modeling: statistical learning and dependent data (springer texts in statistics) (18 resultados)

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Condición: New. pp. XXIII, 608 76 illus., 6 illus. in color. 3 Edition NO-PA16APR2015-KAP.

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Condición: New. pp. XXIII, 608 76 illus., 6 illus. in color.

Condición: New. pp. XXIII, 608 76 illus., 6 illus. in color.

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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Now in its third edition, this companion volume to Ronald Christensen's PlaneAnswers to Complex Questions uses three fundamental concepts from standard linear model theory-best linear prediction, projections, and Mahalanobis distance- to extendstandard linear modeling into the realms of Statistical Learning and Dependent Data. This new edition features a wealth of new and revised content. In StatisticalLearning it delves into nonparametric regression, penalized estimation (regularization),reproducing kernel Hilbert spaces, the kernel trick, and support vector machines. For Dependent Data it uses linear model theory to examine general linear models,linear mixed models, time series, spatial data, (generalized) multivariate linearmodels, discrimination, and dimension reduction. While numerous references toPlane Answers are made throughout the volume, Advanced Linear Modeling can be usedon its own given a solid background in linear models. Accompanying R code for theanalyses is available online.…

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Hardcover. Condición: Brand New. 3rd edition. 634 pages. 9.25x6.10x1.80 inches. In Stock.

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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Now in its third edition, this companion volume to Ronald Christensen's PlaneAnswers to Complex Questions uses three fundamental concepts from standard linear model theory-best linear prediction, projections, and Mahalanobis distance- to extendstandard linear modeling into the realms of Statistical Learning and Dependent Data. This new edition features a wealth of new and revised content. In StatisticalLearning it delves into nonparametric regression, penalized estimation (regularization),reproducing kernel Hilbert spaces, the kernel trick, and support vector machines. For Dependent Data it uses linear model theory to examine general linear models,linear mixed models, time series, spatial data, (generalized) multivariate linearmodels, discrimination, and dimension reduction. While numerous references toPlane Answers are made throughout the volume, Advanced Linear Modeling can be usedon its own given a solid background in linear models. Accompanying R code for theanalyses is available online. 632 pp. Englisch. …

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a collection of methodologies formulated and developed in the framework of linear modelsOffers accompanying R code online for the included analysesFeatures several new chapters, as well as ne.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book will serve as a reference book for graduate students and researchers in statistics. Written by a leading researcher in the field, it discusses advanced topics in the area of linear models.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 632 pp. Englisch.…