Introduction
Functional Data
Motivating Functional Data
Why Is Functional Data Analysis Needed?
Overview of the Book
Implementation of Methodologies
Options for Reading This Book
Nonparametric Smoothers for a Single Curve
Introduction
Local Polynomial Kernel Smoothing
Regression Splines
Smoothing Splines
P-Splines
Reconstruction of Functional Data
Introduction
Reconstruction Methods
Accuracy of LPK Reconstructions
Accuracy of LPK Reconstruction in FLMs
Stochastic Processes
Introduction
Stochastic Processes
x2-Type Mixtures
F-Type Mixtures
One-Sample Problem for Functional Data
ANOVA for Functional Data
Introduction
Two-Sample Problem
One-Way ANOVA
Two-Way ANOVA
Linear Models with Functional Responses
Introduction
Linear Models with Time-Independent Covariates
Linear Models with Time-Dependent Covariates
Ill-Conditioned Functional Linear Models
Introduction
Generalized Inverse Method
Reparameterization Method
Side-Condition Method
Diagnostics of Functional Observations
Introduction
Residual Functions
Functional Outlier Detection
Influential Case Detection
Robust Estimation of Coefficient Functions
Outlier Detection for a Sample of Functions
Heteroscedastic ANOVA for Functional Data
Introduction
Two-Sample Behrens-Fisher Problems
Heteroscedastic One-Way ANOVA
Heteroscedastic Two-Way ANOVA
Test of Equality of Covariance Functions
Introduction
Two-Sample Case
Multi-Sample Case
Bibliography
Index