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Book
ISBN: 2906711365 9782906711365 Year: 1993 Publisher: Montreuil: CISIA-CERESTA,
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Dissertation
Year: 1998 Publisher: [S.l.]: [chez l'auteur],
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Book
ISBN: 1439876517 9781439876510 Year: 2020 Publisher: Boca Raton: CRC,
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The book provides the foundation of time series methods, including linear filters and a geometric approach to prediction. The important paradigm of ARMA models is studied in-depth, as well as frequency domain methods. Entropy and other information theoretic notions are introduced, with applications to time series modeling.
ISBN: 052183127X Year: 2004 Publisher: Cambridge Cambridge University press
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Bootstrap (Statistics) --- Image processing --- Signal processing --- Mathematics
Book
Year: 2012 Publisher: Gaithersburg, MD : U.S. Dept. of Commerce, National Institute of Standards and Technology,
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Book
ISBN: 9781412983532 Year: 1993 Publisher: Newbury Park, [Calif.] ; London : SAGE,
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Using real data examples, Mooney and Duval discuss how to apply bootstrapping when the underlying sampling distribution of the statistics cannot be assumed normal, as well as when the sampling distribution has no analytic solution.
Social sciences --- Bootstrap (Statistics) --- Inference. --- Statistical methods.
Book
ISBN: 1107148421 1280477873 9786610477876 051119529X 0511195958 0511193890 0511331444 0511536712 0511194633 Year: 2004 Publisher: Cambridge ; New York : Cambridge,
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The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample. Such situations are common in signal processing and the bootstrap is especially useful when only a small sample is available or an analytical analysis is too cumbersome or even impossible. This book covers the foundations of the bootstrap, its properties, its strengths and its limitations. The authors focus on bootstrap signal detection in Gaussian and non-Gaussian interference as well as bootstrap model selection. The theory developed in the book is supported by a number of useful practical examples written in MATLAB. The book is aimed at graduate students and engineers, and includes applications to real-world problems in areas such as radar and sonar, biomedical engineering and automotive engineering.
Signal processing --- Image processing --- Bootstrap (Statistics) --- Mathematics.
ISBN: 0387944788 9780387944784 1461225329 Year: 1995 Volume: 98 Publisher: New York (N.Y.) : Springer,
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ISBN: 9780471756217 0471756210 Year: 2008 Publisher: Hoboken: Wiley,
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ISBN: 1107263816 1107266386 1107263263 1107267897 1107264340 1107266823 1107269903 0511802846 9781107266827 0521573912 9780521573917 0521574714 9780521574716 9781107263260 9780511802843 Year: 1997 Publisher: Cambridge Cambridge University Press
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Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This 1997 book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website.
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