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Published by Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030291669 ISBN 13: 9783030291662
Language: English
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Add to basketTaschenbuch. Condition: 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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Add to basketPaperback. Condition: Brand New. 3rd edition. 608 pages. 9.25x6.10x1.26 inches. In Stock.
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Published by Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030291634 ISBN 13: 9783030291631
Language: English
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Add to basketBuch. Condition: 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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Add to basketHardcover. Condition: Brand New. 3rd edition. 634 pages. 9.25x6.10x1.80 inches. In Stock.
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