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Inference for Functional Data with Applications

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Cover of 'Inference for Functional Data with Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Functional data structures
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    Chapter 2 Hilbert space model for functional data
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    Chapter 3 Functional principal components
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    Chapter 4 Canonical correlation analysis
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    Chapter 5 Two sample inference for the mean and covariance functions
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    Chapter 6 Detection of changes in the mean function
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    Chapter 7 Portmanteau test of independence
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    Chapter 8 Functional linear models
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    Chapter 9 Test for lack of effect in the functional linear model
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    Chapter 10 Two sample inference for regression kernels
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    Chapter 11 Tests for error correlation in the functional linear model
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    Chapter 12 A test of significance in functional quadratic regression
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    Chapter 13 Functional autoregressive model
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    Chapter 14 Change point detection in the functional autoregressive process
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    Chapter 15 Determining the order of the functional autoregressive model
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    Chapter 16 Functional time series
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    Chapter 17 Spatially distributed functional data
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    Chapter 18 Consistency of the simple mean and the empirical functional principal components for spatially distributed curves
Attention for Chapter 12: A test of significance in functional quadratic regression
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