Advanced Linear Modeling
Statistical Learning and Dependent Data
Format:Paperback
Publisher:Springer Nature Switzerland AG
Published:8th Jan '21
Currently unavailable, and unfortunately no date known when it will be back
This paperback is available in another edition too:
- Hardback£99.99(9783030291631)
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.
“This book is in my opinion a very valuable resource for researchers since it presents the theoretical foundations of linear models in a unified way while discussing a number of applications. … This book is definitely worth considering for anyone looking for an extensive and thorough treatment of advanced topics in linear modeling.” (Fabio Mainardi, MAA Reviews, May 23, 2021)
ISBN: 9783030291662
Dimensions: unknown
Weight: unknown
608 pages
3rd ed. 2019