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Analysis of Variance for Functional Data
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Analysis of Variance for Functional Data

Book Details

Format Hardback or Cased Book
ISBN-10 1439862737
ISBN-13 9781439862735
Publisher Taylor & Francis Inc
Imprint Chapman & Hall/CRC
Country of Manufacture US
Country of Publication GB
Publication Date Jun 18th, 2013
Print length 410 Pages
Weight 760 grams
Dimensions 24.20 x 16.10 x 2.60 cms
Ksh 30,600.00
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This self-contained book presents up-to-date hypothesis testing methods for functional data analysis. Useful for statistical researchers and practitioners analyzing functional data, it gives both a theoretical and applied treatment of functional data analysis supported by easy-to-use MATLAB® code. The book covers the reconstruction of functional observations, functional ANOVA, functional linear models with functional responses, ill-conditioned functional linear models, diagnostics of functional observations, heteroscedastic ANOVA for functional data, and testing equality of covariance functions. Data sets and MATLAB are available on the author’s website.

Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of functional observations, functional ANOVA, functional linear models with functional responses, ill-conditioned functional linear models, diagnostics of functional observations, heteroscedastic ANOVA for functional data, and testing equality of covariance functions. Although the methodologies presented are designed for curve data, they can be extended to surface data.

Useful for statistical researchers and practitioners analyzing functional data, this self-contained book gives both a theoretical and applied treatment of functional data analysis supported by easy-to-use MATLAB® code. The author provides a number of simple methods for functional hypothesis testing. He discusses pointwise, L2-norm-based, F-type, and bootstrap tests.

Assuming only basic knowledge of statistics, calculus, and matrix algebra, the book explains the key ideas at a relatively low technical level using real data examples. Each chapter also includes bibliographical notes and exercises. Real functional data sets from the text and MATLAB codes for analyzing the data examples are available for download from the author’s website.


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