Advanced Linear Modeling
Statistical Learning and Dependent Data
Authors: Christensen, Ronald
Free Preview- Presents a collection of methodologies formulated and developed in the framework of linear models
- Offers accompanying R code online for the included analyses
- Features several new chapters, as well as new and expanded coverage in this 3rd edition
- Designed to be used independently or in conjunction with the theoretical Plane Answers to Complex Questions
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- About this Textbook
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Now in its third edition, this companion volume to Ronald Christensen’s Plane Answers to Complex Questions uses three fundamental concepts from standard linear model theory—best linear prediction, projections, and Mahalanobis distance— to extend standard linear modeling into the realms of Statistical Learning and Dependent Data.
This new edition features a wealth of new and revised content. In Statistical Learning 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 linear models, discrimination, and dimension reduction. While numerous references to Plane Answers are made throughout the volume, Advanced Linear Modeling can be used on its own given a solid background in linear models. Accompanying R code for the analyses is available online. - About the authors
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Ronald Christensen is a Professor of Statistics at the University of New Mexico, Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics, former Chair of the ASA Section on Bayesian Statistical Science and former Editor of The American Statistician. His book publications include Plane Answers to Complex Questions (Springer 2011), Log-Linear Models and Logistic Regression (Springer 1997), Analysis of Variance, Design, and Regression (1996, 2016), and Bayesian Ideas and Data Analysis (2010, with Johnson, Branscum and Hanson).
- Table of contents (14 chapters)
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Nonparametric Regression
Pages 1-58
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Penalized Estimation
Pages 59-85
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Reproducing Kernel Hilbert Spaces
Pages 87-123
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Covariance Parameter Estimation
Pages 125-159
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Mixed Models and Variance Components
Pages 161-194
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Table of contents (14 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Advanced Linear Modeling
- Book Subtitle
- Statistical Learning and Dependent Data
- Authors
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- Ronald Christensen
- Series Title
- Springer Texts in Statistics
- Copyright
- 2019
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer Nature Switzerland AG
- eBook ISBN
- 978-3-030-29164-8
- DOI
- 10.1007/978-3-030-29164-8
- Hardcover ISBN
- 978-3-030-29163-1
- Softcover ISBN
- 978-3-030-29166-2
- Series ISSN
- 1431-875X
- Edition Number
- 3
- Number of Pages
- XXIII, 608
- Number of Illustrations
- 70 b/w illustrations, 6 illustrations in colour
- Topics
