TY - BOOK ID - 1735906 TI - Wavelet Methods in Statistics with R PY - 2008 SN - 9780387759609 9780387759616 0387759603 0387759611 PB - New York, NY : Springer New York : Imprint: Springer, DB - UniCat KW - Programming KW - Mathematical statistics KW - Statistics. KW - Statistical Theory and Methods. KW - Econometrics. KW - Bioinformatics. KW - Psychometrics. KW - Data Mining and Knowledge Discovery. KW - Data mining. KW - Mathematical statistics. KW - Statistique KW - Exploration de données (Informatique) KW - Bio-informatique KW - Statistique mathématique KW - Econométrie KW - Psychométrie KW - Wavelets (Mathematics) KW - R (Computer program language) KW - Statistics KW - Data mining KW - Bioinformatics KW - Econometrics KW - Psychometrics KW - R (Computer program language). KW - Wavelets (Mathematics). KW - Civil & Environmental Engineering KW - Mathematics KW - Physical Sciences & Mathematics KW - Engineering & Applied Sciences KW - Operations Research KW - Mathematical Statistics KW - Logiciel KW - Computer software KW - Méthode statistique KW - Statistical methods KW - Modèle mathématique KW - Mathematical models KW - Traitement des données KW - Data processing KW - Analyse de séries chronologiques KW - Time series analysis KW - GNU-S (Computer program language) KW - Statistical inference KW - Statistics, Mathematical KW - Wavelet analysis KW - Distribution (Probability theory. KW - Probability Theory and Stochastic Processes. KW - Probabilities KW - Sampling (Statistics) KW - Domain-specific programming languages KW - Harmonic analysis KW - Economics, Mathematical KW - Distribution functions KW - Frequency distribution KW - Characteristic functions KW - Algorithmic knowledge discovery KW - Factual data analysis KW - KDD (Information retrieval) KW - Knowledge discovery in data KW - Knowledge discovery in databases KW - Mining, Data KW - Database searching KW - Measurement, Mental KW - Measurement, Psychological KW - Psychological measurement KW - Psychological scaling KW - Psychological statistics KW - Psychology KW - Psychometry (Psychophysics) KW - Scaling, Psychological KW - Psychological tests KW - Scaling (Social sciences) KW - Bio-informatics KW - Biological informatics KW - Biology KW - Information science KW - Computational biology KW - Systems biology KW - Measurement KW - Scaling KW - Methodology KW - Probabilities. KW - Statistics . KW - Statistical analysis KW - Statistical data KW - Statistical science KW - Probability KW - Combinations KW - Chance KW - Least squares KW - Risk UR - https://www.unicat.be/uniCat?func=search&query=sysid:1735906 AB - Wavelet methods have recently undergone a rapid period of development with important implications for a number of disciplines including statistics. This book has three main objectives: (i) providing an introduction to wavelets and their uses in statistics; (ii) acting as a quick and broad reference to many developments in the area; (iii) interspersing R code that enables the reader to learn the methods, to carry out their own analyses, and further develop their own ideas. The book code is designed to work with the freeware R package WaveThresh4, but the book can be read independently of R. The book introduces the wavelet transform by starting with the simple Haar wavelet transform, and then builds to consider more general wavelets, complex-valued wavelets, non-decimated transforms, multidimensional wavelets, multiple wavelets, wavelet packets, boundary handling, and initialization. Later chapters consider a variety of wavelet-based nonparametric regression methods for different noise models and designs including density estimation, hazard rate estimation, and inverse problems; the use of wavelets for stationary and non-stationary time series analysis; and how wavelets might be used for variance estimation and intensity estimation for non-Gaussian sequences. The book is aimed both at Masters/Ph.D. students in a numerate discipline (such as statistics, mathematics, economics, engineering, computer science, and physics) and postdoctoral researchers/users interested in statistical wavelet methods. Guy Nason is Professor of Statistics at the University of Bristol. He has been actively involved in the development of various wavelet methods in statistics since 1993. He was awarded the Royal Statistical Society’s 2001 Guy Medal in Bronze for work on wavelets in statistics. He was the author of the first, free, generally available wavelet package for statistical purposes in S and R (WaveThresh2). ER -