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Inference for Functional Data with Applications

Overview of attention for book
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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Chapter title
A test of significance in functional quadratic regression
Chapter number 12
Book title
Inference for Functional Data with Applications
Published by
Springer, New York, NY, January 2012
DOI 10.1007/978-1-4614-3655-3_12
Book ISBNs
978-1-4614-3654-6, 978-1-4614-3655-3
Authors

Lajos Horváth, Piotr Kokoszka

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Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Unknown 1 100%

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