Advanced Linear Modeling: Statistical Learning And Dependent Data

Description

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. Front Matter ....Pages i-xxiii Nonparametric Regression (Ronald Christensen)....Pages 1-58 Penalized Estimation (Ronald Christensen)....Pages 59-85 Reproducing Kernel Hilbert Spaces (Ronald Christensen)....Pages 87-123 Covariance Parameter Estimation (Ronald Christensen)....Pages 125-159 Mixed Models and Variance Components (Ronald Christensen)....Pages 161-194 Frequency Analysis of Time Series (Ronald Christensen)....Pages 195-246 Time Domain Analysis (Ronald Christensen)....Pages 247-319 Linear Models for Spatial Data: Kriging (Ronald Christensen)....Pages 321-355 Multivariate Linear Models: General (Ronald Christensen)....Pages 357-388 Multivariate Linear Models: Applications (Ronald Christensen)....Pages 389-422 Generalized Multivariate Linear Models and Longitudinal Data (Ronald Christensen)....Pages 423-455 Discrimination and Allocation (Ronald Christensen)....Pages 457-501 Binary Discrimination and Regression (Ronald Christensen)....Pages 503-531 Principal Components, Classical Multidimensional Scaling, and Factor Analysis (Ronald Christensen)....Pages 533-574 Back Matter ....Pages 575-608