Wavelet applications in economics and finance, 

Автор: Ross Stephen
Название: Core principles and applications of Corporate Finance, global edition
ISBN: 0071221166 ISBN-13(EAN): 9780071221160
Издательство: McGraw-Hill
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Цена: 8578.00 р.
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Описание: Conveys important corporate finance concepts and applications. This text distills the subject of corporate finance down to its core, while also maintaining a decidedly modern approach.

Автор: Sriboonchita
Название: Stochastic Dominance and Applications to Finance, Risk and Economics
ISBN: 1138117994 ISBN-13(EAN): 9781138117990
Издательство: Taylor&Francis
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Цена: 10717.00 р.
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Описание: This accessible guide helps readers build a useful repertoire of mathematical tools in decision making under uncertainty, especially in investment science. It uses real data and statistical procedures to show how SD theory is applied in financial situations, introduces utility theory for decision making under risk and discusses research issues.

Автор: Marco Gallegati; Willi Semmler
Название: Wavelet Applications in Economics and Finance
ISBN: 3319382993 ISBN-13(EAN): 9783319382999
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book deals with the application of wavelet and spectral methods for the analysis of nonlinear and dynamic processes in economics and finance. It reflects some of the latest developments in the area of wavelet methods applied to economics and finance.

Автор: Anestis Antoniadis; Georges Oppenheim
Название: Wavelets and Statistics
ISBN: 0387945644 ISBN-13(EAN): 9780387945644
Издательство: Springer
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Цена: 16769.00 р.
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Описание: Proceedings of a conference held at Villard de Lans, France, in 1994. The material is wide in scope and ranges from the development of new tools for nonparametric curve estimation to applied problems such as detection of transients in signal processing and image segmentation.

Автор: Ramazan Gen?§ay
Название: An Introduction to Wavelets and Other Filtering Methods in Financ
ISBN: 0122796705 ISBN-13(EAN): 9780122796708
Издательство: Elsevier Science
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Цена: 17685.00 р.
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Описание: Presents a unified view of filtering techniques with a focus on wavelet analysis in finance and economics. This title emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series.

Автор: Pedro A. Morettin; Alu?sio Pinheiro; Brani Vidakov
Название: Wavelets in Functional Data Analysis
ISBN: 3319596225 ISBN-13(EAN): 9783319596228
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book presents wavelets in functional data analysis, offering a glimpse of problems in which they can be applied, including tumor analysis, functional magnetic resonance and meteorological data.

Автор: Andrew Bruce; Hong-Ye Gao
Название: Applied Wavelet Analysis with S-PLUS
ISBN: 0387947140 ISBN-13(EAN): 9780387947143
Издательство: Springer
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Цена: 15372.00 р.
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Описание: Furthermore, in addition to wavelets, a whole range of related signal processing techniques such as wavelet packets, local cosine analysis, and matching pursuits are covered, and applications of wavelet analysis are illustrated -including nonparametric function estimation, digital image compression, and time-frequency signal analysis.

Автор: Peter M?ller; Brani Vidakovic
Название: Bayesian Inference in Wavelet-Based Models
ISBN: 0387988858 ISBN-13(EAN): 9780387988856
Издательство: Springer
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Цена: 20263.00 р.
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Описание: Chapters in Part II explore different approaches to prior modeling, using independent priors. Papers in the Part III discuss decision theoretic aspects of such prior models. In Part IV, some aspects of prior modeling using priors that account for dependence are explored.

Автор: Wolfgang H?rdle; Gerard Kerkyacharian; Dominique P
Название: Wavelets, Approximation, and Statistical Applications
ISBN: 0387984534 ISBN-13(EAN): 9780387984537
Издательство: Springer
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Цена: 16769.00 р.
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Описание: The mathematical theory of ondelettes (wavelets) was developed by Yves Meyer and many collaborators about 10 years ago. Five years ago wavelet theory progressively appeared to be a power- ful framework for nonparametric statistical problems.