Inference for Functional Data with Applications

Name: Inference for Functional Data with Applications
Brand: Springer
SKU: 9781489990525
Price: 11643.0 INR
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by Lajos Horváth

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ISBN13: 9781489990525
Binding: Paperback
Subject: N/A
Publisher: Springer
Publisher Imprint: Springer
Publication Date: June 11, 2014
Pages: 422
Original Price: EUR 159.99
Language: English
Edition: 2012
Item Weight: 618 grams
BISAC Subject(s): Probability & Statistics / General, Statistics, and Econometrics

About The Book

From the Back Cover

This book presents recently developed statistical methods and theory required for the application of the tools of functional data analysis to problems arising in geosciences, finance, economics and biology. It is concerned with inference based on second order statistics, especially those related to the functional principal component analysis. While it covers inference for independent and identically distributed functional data, its distinguishing feature is an in depth coverage of dependent functional data structures, including functional time series and spatially indexed functions. Specific inferential problems studied include two sample inference, change point analysis, tests for dependence in data and model residuals and functional prediction. All procedures are described algorithmically, illustrated on simulated and real data sets, and supported by a complete asymptotic theory.

The book can be read at two levels. Readers interested primarily in methodology will find detailed descriptions of the methods and examples of their application. Researchers interested also in mathematical foundations will find carefully developed theory. The organization of the chapters makes it easy for the reader to choose an appropriate focus. The book introduces the requisite, and frequently used, Hilbert space formalism in a systematic manner. This will be useful to graduate or advanced undergraduate students seeking a self-contained introduction to the subject. Advanced researchers will find novel asymptotic arguments.

About The Author

Lajos Horváth is Professor of Mathematics at the University of Utah. He has served on the editorial boards of Statistics & Probability Letters, Journal of Statistical Planning and Inference and Journal of Time Series Econometrics. He has coauthored more than 250 research papers and 3 books, including Weighted Approximations in Probability and Statistics and Limit Theorems in Change-Point Analysis (both with Miklós Csörgö).

Piotr Kokoszka is Professor of Statistics at Colorado State University. He has served on the editorial boards of the journals Statistical Modelling and Computational Statistics. He has coauthored over 100 papers in areas of statistics and its applications focusing on dependent data.

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