Wavelet Methods In Statistics With R
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Wavelet Methods In Statistics With R
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Author : Guy Nason
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-25
Wavelet Methods In Statistics With R written by Guy Nason and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-25 with Mathematics categories.
This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.
Wavelet Methods In Statistics With R
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Author : G. P. Nason
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-11
Wavelet Methods In Statistics With R written by G. P. Nason and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-11 with Business & Economics categories.
This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.
Wavelet Methods In Statistics Withr
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Author : Guy P. Nason
language : en
Publisher:
Release Date : 2010
Wavelet Methods In Statistics Withr written by Guy P. Nason and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Advanced Data Mining And Applications
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Author : Jianxin Li
language : en
Publisher: Springer Nature
Release Date : 2019-11-16
Advanced Data Mining And Applications written by Jianxin Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Computers categories.
This book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.
Advanced Data Mining And Applications
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Author : Weitong Chen
language : en
Publisher: Springer Nature
Release Date : 2022-11-23
Advanced Data Mining And Applications written by Weitong Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-23 with Computers categories.
The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Statistical Analysis Of Financial Data In R
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Author : René Carmona
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-13
Statistical Analysis Of Financial Data In R written by René Carmona and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-13 with Business & Economics categories.
Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns of risk management are addressed by the study of extreme values, the fitting of distributions with heavy tails, the computation of values at risk (VaR), and other measures of risk. Principal component analysis (PCA), smoothing, and regression techniques are applied to the construction of yield and forward curves. Time series analysis is applied to the study of temperature options and nonparametric estimation. Nonlinear filtering is applied to Monte Carlo simulations, option pricing and earnings prediction. This textbook is intended for undergraduate students majoring in financial engineering, or graduate students in a Master in finance or MBA program. It is sprinkled with practical examples using market data, and each chapter ends with exercises. Practical examples are solved in the R computing environment. They illustrate problems occurring in the commodity, energy and weather markets, as well as the fixed income, equity and credit markets. The examples, experiments and problem sets are based on the library Rsafd developed for the purpose of the text. The book should help quantitative analysts learn and implement advanced statistical concepts. Also, it will be valuable for researchers wishing to gain experience with financial data, implement and test mathematical theories, and address practical issues that are often ignored or underestimated in academic curricula. This is the new, fully-revised edition to the book Statistical Analysis of Financial Data in S-Plus. René Carmona is the Paul M. Wythes '55 Professor of Engineering and Finance at Princeton University in the department of Operations Research and Financial Engineering, and Director of Graduate Studies of the Bendheim Center for Finance. His publications include over one hundred articles and eight books in probability and statistics. He was elected Fellow of the Institute of Mathematical Statistics in 1984, and of the Society for Industrial and Applied Mathematics in 2010. He is on the editorial board of several peer-reviewed journals and book series. Professor Carmona has developed computer programs for teaching statistics and research in signal analysis and financial engineering. He has worked for many years on energy, the commodity markets and more recently in environmental economics, and he is recognized as a leading researcher and expert in these areas.
Discrete Wavelet Transforms
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Author : Dr. Awad Al-Asmari
language : en
Publisher: BoD – Books on Demand
Release Date : 2013-02-06
Discrete Wavelet Transforms written by Dr. Awad Al-Asmari and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-06 with Computers categories.
Discrete Wavelet Transform is a wavelet (DWT) transform that is widely used in numerical and functional analysis. Its key advantage over more traditional transforms, such as the Fourier transform, lies in its ability to offer temporal resolution, i.e. it captures both frequency and location (or time) information. This book presents a succinct compendium of some of the more recent variants of DWTs and their use to come up with solutions to an array of problems transcending the traditional application areas of image/video processing and security to the relatively newer areas of medicine, artificial intelligence, power systems and telecommunications. The first of the two sections of this book contains three chapters devoted to traditional applications of DWTs in digital image compression, copyright protection and video resolution enhancement. The second section, comprising of five chapters, is devoted to variants of the DWT and their applications in humanoid-robot vision systems; modeling and simulation recognition of physiological and behavioral traits through human gait and facial images; assessment of agitation and sedation in intensive care patients; maximization of power control systems; and, finally, in demodulation of FM data in free-space optical control systems.
Wavelet Methods For Time Series Analysis
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Author : Donald B. Percival
language : en
Publisher: Cambridge University Press
Release Date : 2000
Wavelet Methods For Time Series Analysis written by Donald B. Percival and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
This introduction to wavelet analysis 'from the ground level and up', and to wavelet-based statistical analysis of time series focuses on practical discrete time techniques, with detailed descriptions of the theory and algorithms needed to understand and implement the discrete wavelet transforms. Numerous examples illustrate the techniques on actual time series. The many embedded exercises - with complete solutions provided in the Appendix - allow readers to use the book for self-guided study. Additional exercises can be used in a classroom setting. A Web site offers access to the time series and wavelets used in the book, as well as information on accessing software in S-Plus and other languages. Students and researchers wishing to use wavelet methods to analyze time series will find this book essential.
Semiparametric Regression With R
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Author : Jaroslaw Harezlak
language : en
Publisher: Springer
Release Date : 2018-12-12
Semiparametric Regression With R written by Jaroslaw Harezlak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with Mathematics categories.
This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.
Noise Reduction By Wavelet Thresholding
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Author : Maarten Jansen
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Noise Reduction By Wavelet Thresholding written by Maarten Jansen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Wavelet methods have become a widely spread tool in signal and image process ing tasks. This book deals with statistical applications, especially wavelet based smoothing. The methods described in this text are examples of non-linear and non parametric curve fitting. The book aims to contribute to the field both among statis ticians and in the application oriented world (including but not limited to signals and images). Although it also contains extensive analyses of some existing methods, it has no intention whatsoever to be a complete overview of the field: the text would show too much bias towards my own algorithms. I rather present new material and own insights in the questions involved with wavelet based noise reduction. On the other hand, the presented material does cover a whole range of methodologies, and in that sense, the book may serve as an introduction into the domain of wavelet smoothing. Throughout the text, three main properties show up ever again: sparsity, locality and multiresolution. Nearly all wavelet based methods exploit at least one of these properties in some or the other way. These notes present research results of the Belgian Programme on Interuniver sity Poles of Attraction, initiated by the Belgian State, Prime Minister's Office for Science, Technology and Culture. The scientific responsibility rests with me. My research was financed by a grant (1995 - 1999) from the Flemish Institute for the Promotion of Scientific and Technological Research in the Industry (IWT).