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| modern spectrum analysis of time series: Modern Spectrum Analysis of Time Series Prabhakar S. Naidu, 1995-10-25 Spectrum analysis can be considered as a topic in statistics as well as a topic in digital signal processing (DSP). This book takes a middle course by emphasizing the time series models and their impact on spectrum analysis. The text begins with elements of probability theory and goes on to introduce the theory of stationary stochastic processes. The depth of coverage is extensive. Many topics of concern to spectral characterization of Gaussian and non-Gaussian time series, scalar and vector time series are covered. A section is devoted to the emerging areas of non-stationary and cyclostationary time series. The book is organized more as a textbook than a reference book. Each chapter includes many examples to illustrate the concepts described. Several exercises are included at the end of each chapter. The level is appropriate for graduate and research students. |
| modern spectrum analysis of time series: Singular Spectrum Analysis for Time Series Nina Golyandina, Anatoly Zhigljavsky, 2013-01-19 Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA seeks to decompose the original series into a sum of a small number of interpretable components such as trend, oscillatory components and noise. It is based on the singular value decomposition of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity are assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability. The present book is devoted to the methodology of SSA and shows how to use SSA both safely and with maximum effect. Potential readers of the book include: professional statisticians and econometricians, specialists in any discipline in which problems of time series analysis and forecasting occur, specialists in signal processing and those needed to extract signals from noisy data, and students taking courses on applied time series analysis. |
| modern spectrum analysis of time series: Analysis of Time Series Structure Nina Golyandina, Vladimir Nekrutkin, Anatoly A Zhigljavsky, 2001-01-23 Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing. However, despite the promise it holds for time series applications in other disciplines, SSA is not widely known among statisticians and econometrists, and although the basic SSA algorithm looks simple, understanding what it does and where its pitfalls lay is by no means simple. Analysis of Time Series Structure: SSA and Related Techniques provides a careful, lucid description of its general theory and methodology. Part I introduces the basic concepts, and sets forth the main findings and results, then presents a detailed treatment of the methodology. After introducing the basic SSA algorithm, the authors explore forecasting and apply SSA ideas to change-point detection algorithms. Part II is devoted to the theory of SSA. Here the authors formulate and prove the statements of Part I. They address the singular value decomposition (SVD) of real matrices, time series of finite rank, and SVD of trajectory matrices. Based on the authors' original work and filled with applications illustrated with real data sets, this book offers an outstanding opportunity to obtain a working knowledge of why, when, and how SSA works. It builds a strong foundation for successfully using the technique in applications ranging from mathematics and nonlinear physics to economics, biology, oceanology, social science, engineering, financial econometrics, and market research. |
| modern spectrum analysis of time series: Modern Spectrum Analysis Donald G. Childers, 1978 |
| modern spectrum analysis of time series: Spectral Analysis for Univariate Time Series Donald B. Percival, Andrew T. Walden, 2020-03-19 Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website. |
| modern spectrum analysis of time series: Spectral Analysis of Time Series Bernard Harris, 1967 |
| modern spectrum analysis of time series: Analysis of Geophysical Potential Fields P.S. Naidu, M.P. Mathew, 1998-06-19 When some useful information is hidden behind a mass of unwanted information we often resort to information processing used in its broad sense or specifically to signal processing when the useful information is a waveform. In geophysical surveys, in particular in aeromagnetic and gravity surveys, from the measured field it is often difficult to say much about any one specific target unless it is close to the surface and well isolated from the rest. The digital signal processing approach would enable us to bring out the underlying model of the source, that is, the geological structure. Some of the tools of dsp such as digital filtering, spectrum estimation, inversion, etc., have found extensive applications in aeromagnetic and gravity map analysis. There are other emerging applications of dsp in the area of inverse filtering, three dimensional visualization, etc.The purpose of this book is to bring numerous tools of dsp to the geophysical community, in particular, to those who are entering the geophysical profession. Also the practicing geophysicists, involved in the aeromagnetic and gravity data analysis, using the commercially available software packages, will find this book useful in answering their questions on why and how?. It is hoped that such a background would enable the practising geophysicists to appreciate the prospects and limitations of the dsp in extracting useful information from the potential field maps. The topics covered are: potential field signals and models, digital filtering in two dimensions, spectrum estimation and application, parameter estimation with error bounds. |
| modern spectrum analysis of time series: Spectral Analysis for Physical Applications Donald B. Percival, Andrew T. Walden, 1993-06-03 This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography. |
| modern spectrum analysis of time series: Digital Signal Processing and Spectral Analysis for Scientists Silvia Maria Alessio, 2015-12-09 This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data. |
| modern spectrum analysis of time series: Digital Spectral Analysis S. Lawrence Marple, Jr., 2019-03-20 Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral estimation of discrete-time or discrete-space sequences derived by sampling continuous-time or continuous-space signals. The treatment emphasizes the behavior of each spectral estimator for short data records and provides over 40 techniques described and available as implemented MATLAB functions. In addition to summarizing classical spectral estimation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. Topics include Prony's method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and two-dimensional methods. Suitable for advanced undergraduates and graduate students of electrical engineering — and for scientific use in the signal processing application community outside of universities — the treatment's prerequisites include some knowledge of discrete-time linear system and transform theory, introductory probability and statistics, and linear algebra. 1987 edition. |
| modern spectrum analysis of time series: New Tools of Economic Dynamics Jacek Leskow, 2005-07-13 New Tools of Economic Dynamics gives an introduction and overview of recently developed methods and tools, most of them developed outside economics, to deal with the qualitative analysis of economic dynamics. It reports the results of a three-year research project by a European and Latin American network on the intersection of economics with mathematical, statistical, and computational methods and techniques. Focusing upon the evolution and manifold structure of complex dynamic phenomena, the book reviews and shows applications of a variety of tools, such as symbolic and coded dynamics, interacting agents models, microsimulation in econometrics, large-scale system analysis, and dynamical systems theory. It shows the potential of a comprehensive analysis of growth, fluctuations, and structural change along the lines indicated by pioneers like Harrod, Haavelmo, Hicks, Goodwin, Morishima, and it highlights the explanatory power of the qualitative approach they initiated. |
| modern spectrum analysis of time series: Speech Spectrum Analysis Sean A. Fulop, 2011-05-26 The accurate determination of the speech spectrum, particularly for short frames, is commonly pursued in diverse areas including speech processing, recognition, and acoustic phonetics. With this book the author makes the subject of spectrum analysis understandable to a wide audience, including those with a solid background in general signal processing and those without such background. In keeping with these goals, this is not a book that replaces or attempts to cover the material found in a general signal processing textbook. Some essential signal processing concepts are presented in the first chapter, but even there the concepts are presented in a generally understandable fashion as far as is possible. Throughout the book, the focus is on applications to speech analysis; mathematical theory is provided for completeness, but these developments are set off in boxes for the benefit of those readers with sufficient background. Other readers may proceed through the main text, where the key results and applications will be presented in general heuristic terms, and illustrated with software routines and practical show-and-tell discussions of the results. At some points, the book refers to and uses the implementations in the Praat speech analysis software package, which has the advantages that it is used by many scientists around the world, and it is free and open source software. At other points, special software routines have been developed and made available to complement the book, and these are provided in the Matlab programming language. If the reader has the basic Matlab package, he/she will be able to immediately implement the programs in that platform---no extra toolboxes are required. |
| modern spectrum analysis of time series: Time Series Analysis and Its Applications Robert H. Shumway, David S. Stoffer, 2013-03-14 The goals of this book are to develop an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing data, and still maintain a commitment to theoretical integrity, as exemplified by the seminal works of Brillinger (1981) and Hannan (1970) and the texts by Brockwell and Davis (1991) and Fuller (1995). The advent of more powerful computing, es pecially in the last three years, has provided both real data and new software that can take one considerably beyond the fitting of·simple time domain mod els, such as have been elegantly described in the landmark work of Box and Jenkins (1970). The present book is designed to be useful as a text for courses in time series on several different levels and as a reference work for practition ers facing the analysis of time-correlated data in the physical, biological, and social sciences. We believe the book will be useful as a text at both the undergraduate and graduate levels. An undergraduate course can be accessible to students with a background in regression analysis and might include Sections 1. 1-1. 8, 2. 1-2. 9, and 3. 1-3. 8. Similar courses have been taught at the University of California (Berkeley and Davis) in the past using the earlier book on applied time series analysis by Shumway (1988). Such a course is taken by undergraduate students in mathematics, economics, and statistics and attracts graduate students from the agricultural, biological, and environmental sciences. |
| modern spectrum analysis of time series: Maximum-Entropy and Bayesian Spectral Analysis and Estimation Problems C.R. Smith, G. Erickson, 2012-12-06 This volume has its origin in the third ·Workshop on Maximum-Entropy and Bayesian Methods in Applied Statistics,· held at the University of Wyoming, August 1 to 4, 1983. It was anticipated that the proceedings of this workshop could not be prepared in a timely fashion, so most of the papers were not collected until a year or so ago. Because most of the papers are in the nature of advancing theory or solving specific problems, as opposed to status reports, it is believed that the contents of this volume will be of lasting interest to the Bayesian community. The workshop was organized to bring together researchers from differ ent fields to examine critically maximum-entropy and Bayesian methods in science, engineering, medicine, economics, and other disciplines. Some of the papers were chosen specifically to kindle interest in new areas that may offer new tools or insight to the reader or to stimulate work on pressing problems that appear to be ideally suited to the maximum-entropy or Bayes ian method. |
| modern spectrum analysis of time series: Fundamentals of Signal Processing in Generalized Metric Spaces Andrey Popoff, 2022-04-19 Exploring the interrelations between generalized metric spaces, lattice-ordered groups, and order statistics, the book contains a new algebraic approach to Signal Processing Theory. It describes mathematical concepts and results important in the development, analysis, and optimization of signal processing algorithms intended for various applications. The book offers a solution of large-scale Signal Processing Theory problems of increasing both signal processing efficiency under prior uncertainty conditions and signal processing rate that is provided by multiplication-free signal processing algorithms based on lattice-ordered group operations. From simple basic relationships to computer simulation, the text covers a wide range of new mathematical techniques essential for understanding the proposed signal processing algorithms developed for solving the following problems: signal parameter and spectral estimation, signal filtering, detection, classification, and resolution; array signal processing; demultiplexing and demodulation in multi-channel communication systems and multi-station networks; wavelet analysis of 1D/ 2D signals. Along with discussing mathematical aspects, each chapter presents examples illustrating operation of signal processing algorithms developed for various applications. The book helps readers understand relations between known classic and obtained results as well as recent research trends in Signal Processing Theory and its applications, providing all necessary mathematical background concerning lattice-ordered groups to prepare readers for independent work in the marked directions including more advanced research and development. |
| modern spectrum analysis of time series: Modern Spectral Analysis with Geophysical Applications Markus Båth, 1995 |
| modern spectrum analysis of time series: Fourier Analysis of Time Series Peter Bloomfield, 2004-03-22 A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample exercises acquaint readers with Fourier analysis and its applications. The Second Edition: * Devotes an entire chapter to complex demodulation * Treats harmonic regression in two separate chapters * Features a more succinct discussion of the fast Fourier transform * Uses S-PLUS commands (replacing FORTRAN) to accommodate programming needs and graphic flexibility * Includes Web addresses for all time series data used in the examples An invaluable reference for statisticians seeking to expand their understanding of frequency domain methods, Fourier Analysis of Time Series, Second Edition also provides easy access to sophisticated statistical tools for scientists and professionals in such areas as atmospheric science, oceanography, climatology, and biology. |
| modern spectrum analysis of time series: Spectral Analysis in Engineering Grant Hearn, Andrew Metcalfe, 1995-08-17 This text provides a thorough explanation of the underlying principles of spectral analysis and the full range of estimation techniques used in engineering. The applications of these techniques are demonstrated in numerous case studies, illustrating the approach required and the compromises to be made when solving real engineering problems. The principles outlined in these case studies are applicable over the full range of engineering disciplines and all the reader requires is an understanding of elementary calculus and basic statistics. The realistic approach and comprehensive nature of this text will provide undergraduate engineers and physicists of all disciplines with an invaluable introduction to the subject and the detailed case studies will interest the experienced professional. - No more than a knowledge of elementary calculus, and basic statistics and probability is needed - Accessible to undergraduates at any stage of their courses - Easy and clear to follow |
| modern spectrum analysis of time series: Time-Series Analysis and Cyclostratigraphy Graham P. Weedon, 2005-09-15 An essential reference for researchers, and suitable for senior undergraduate and graduate courses in environmental science, palaeoceanography and geology. |
| modern spectrum analysis of time series: Underwater Acoustics and Signal Processing L. Bjørnø, 2012-12-06 The comprehensive research activity around the World in the fields of Underwater Acoustics and Signal Processing being strongly supported by new experimental technique and equipment and by the parallel fast developments in computer technology and solid state devices, which has led to a rapidly reducing cost of digital processing thus enabling more complex processing to be carried out economically, emphasize how necessary it is at intervals of a few years through a NATO Advanced Study Institute (NATO ASI) and guided by leading experts to study the conquests in the fields of Underwater Acoustics and Signal Processing. This need of study is moreover stressed by the interdisciplina rity of Underwater Acoustics and Signal Processing, where a strong impact from other branches of science, - Geophysics, Radioastronomy, Bioengineering, Telecommunication, Seismology, Space Research etc. - is taking place, which makes it an extre mely difficult task for scientists to follow-up the development in all its phases and to preserve the general view of its rapid ly increasing number of possibilities. The present Proceedings of the NATO ASI held in Copenhagen during August 1980 join the series of proceedings of NATO summer schools on Underwater Acoustics and Signal Processing held during the past 20 years. The equality and the fusion of the individual research fields of Underwater Acoustics and Signal Processing and the separate introduction of advanced research results from other scientific areas related to underwater acoustics such as transducers characterize the subject matter of this NATO ASI. |
| modern spectrum analysis of time series: Advanced Digital Signal Processing and Noise Reduction Saeed V. Vaseghi, 2006-02-03 Signal processing plays an increasingly central role in the development of modern telecommunication and information processing systems, with a wide range of applications in areas such as multimedia technology, audio-visual signal processing, cellular mobile communication, radar systems and financial data forecasting. The theory and application of signal processing deals with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and hence, noise reduction and the removal of channel distortion is an important part of a signal processing system. Advanced Digital Signal Processing and Noise Reduction, Third Edition, provides a fully updated and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Noise is the eternal bane of communications engineers, who are always striving to find new ways to improve the signal-to-noise ratio in communications systems and this resource will help them with this task. * Features two new chapters on Noise, Distortion and Diversity in Mobile Environments and Noise Reduction Methods for Speech Enhancement over Noisy Mobile Devices. * Topics discussed include: probability theory, Bayesian estimation and classification, hidden Markov models, adaptive filters, multi-band linear prediction, spectral estimation, and impulsive and transient noise removal. * Explores practical solutions to interpolation of missing signals, echo cancellation, impulsive and transient noise removal, channel equalisation, HMM-based signal and noise decomposition. This is an invaluable text for senior undergraduates, postgraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also appeal to engineers in telecommunications and audio and signal processing industries. |
| modern spectrum analysis of time series: Encyclopaedia of Mathematics Michiel Hazewinkel, 1988 V.1. A-B v.2. C v.3. D-Feynman Measure. v.4. Fibonaccimethod H v.5. Lituus v.6. Lobachevskii Criterion (for Convergence)-Optical Sigman-Algebra. v.7. Orbi t-Rayleigh Equation. v.8. Reaction-Diffusion Equation-Stirling Interpolation Fo rmula. v.9. Stochastic Approximation-Zygmund Class of Functions. v.10. Subject Index-Author Index. |
| modern spectrum analysis of time series: Concise Encyclopedia of Modelling and Simulation D.P. Atherton, P. Borne, 2013-10-22 The Concise Encyclopedia of Modelling & Simulation contains 172 alphabetically arranged articles describing the modelling and simulation of physical systems. The emphasis is on mathematical models and their various forms, although other types of models, such as knowledge-based, linguistics-based, graphical and data-based, are also discussed. The articles are revised from the Systems & Control Encyclopedia, and many newly commissioned articles are included describing recent developments in the field. Articles on identification cover all aspects of this problem, from the use and choice of specific test signals to problems of model order and the many algorithms and approaches to parameter estimation. Computational techniques, such as the finite-element method, that play an important role in analyzing nonlinear models are covered. Articles outline the development of simulation, consider currently available simulation languages, describe applications and cover current developments in the area. Where appropriate, illustrations and tables are included to clarify particular topics. This encyclopedia will be a valuable reference source for all practising engineers, researchers and postgraduate students in the field of modelling and simulation. |
| modern spectrum analysis of time series: Business Cycles and Depressions David Glasner, 2013-12-16 Experts define, review, and evaluate economic fluctuations Economic and business uncertainty dominate today's economic analyses. This new Encyclopedia illuminates the subject by offering 323 original articles on every major aspect of business cycles, fluctuations, financial crises, recessions, and depressions. The work of more than 200 experts, including many of the leading researchers in the field, the articles cover a broad range of subjects, including capsule biographies of leading economists born before 1920. Individual entries explore banking panics, the cobweb cycle, consumer durables, the depression of 1937-1938, Otto Eckstein, Friedrich Engels, experimental price bubbles, forced savings, lass-Steagall Act, Friedrich hagen, qualitative indicators, use of macro-econometric models, monetary neutrality, Phillips Curve, Paul Samuelson, Say's law, supply-side recessions, James Tokin, trend and random wages, Thorstein Veblen, worker-job turnover, and more. |
| modern spectrum analysis of time series: Data-Centric Business and Applications Tamara Radivilova, Dmytro Ageyev, Natalia Kryvinska, 2020-06-20 This book addresses the challenges and opportunities of information/data processing and management. It also covers a range of methods, techniques and strategies for making it more efficient, approaches to increasing its usage, and ways to minimize information/data loss while improving customer satisfaction. Information and Communication Technologies (ICTs) and the Service Systems associated with them have had an enormous impact on businesses and our day-to-day lives over the past three decades, and continue to do so. This development has led to the emergence of new application areas and relevant disciplines, which in turn present new challenges and opportunities for service system usage. The book provides practical insights into various aspects of ICT technologies for service systems: Techniques for information/data processing and modeling in service systems Strategies for the provision of information/data processing and management Methods for collecting and analyzing information/data Applications, benefits, and challenges of service system implementation Solutions to increase the performance of various service systems using the latest ICT technologies |
| modern spectrum analysis of time series: Rhythms in Biology and Other Fields of Application Société mathématique de France, Société mathématique de France. Journées, 1983-06 This volume contains most of the talks presented at the Journ~es de la Soci~t~ Math~ma~ique de France entitled Rhythms in Biology and other fields of application -Determi nistic and Stochastic Approaches held in Luminy from the 14th th to the 18 of September 1981. The aim of our meeting was to bring together scien tists from different disciplines to discuss a common topic and to stimulate exchanges between participants. We hope that this goal was reached. This volume is divided into four chapters. In each one the papers are arranged in alphabetical order by first author. Chapters one and two contain papers devoted to descrip tion or modelling of rhythmic biolog.ical phenomena. Chapters three and four deal with models for the study of rhythms invol ving the use of deterministic or stochastic tools capable of fruitful transfer to Biology. We are pleased that these Proceedings appear in a series which constitutes an interface between Biologists and Mathema ticians. We are indebted to all who provided us with their help, particularly the Centre International de Rencontres Math~matiques (C.I.R.M.) at Luminy, the Soci~t~ Mathematique de France (S.M.F.), the Delegation aux Relations Universitaires Internationales (D.R.U.I.) and the Laboratoire d'Informatique et de Math~matiques Appliquees de Grenoble (I.M.A.G.). Special thanks are due to Mrs. A. Litman for her dedi cation and her efficiency throughout the organization of this meeting. G~enobie, Vecembe~ 1982. |
| modern spectrum analysis of time series: Optimal Filtering V.N. Fomin, 2012-12-06 This book is devoted to an investigation of some important problems of mod ern filtering theory concerned with systems of 'any nature being able to per ceive, store and process an information and apply it for control and regulation'. (The above quotation is taken from the preface to [27]). Despite the fact that filtering theory is l'argely worked out (and its major issues such as the Wiener-Kolmogorov theory of optimal filtering of stationary processes and Kalman-Bucy recursive filtering theory have become classical) a development of the theory is far from complete. A great deal of recent activity in this area is observed, researchers are trying consistently to generalize famous results, extend them to more broad classes of processes, realize and justify more simple procedures for processing measurement data in order to obtain more efficient filtering algorithms. As to nonlinear filter ing, it remains much as fragmentary. Here much progress has been made by R. L. Stratonovich and his successors in the area of filtering of Markov processes. In this volume an effort is made to advance in certain of these issues. The monograph has evolved over many years, coming of age by stages. First it was an impressive job of gathering together the bulk of the impor tant contributions to estimation theory, an understanding and moderniza tion of some of its results and methods, with the intention of applying them to recursive filtering problems. |
| modern spectrum analysis of time series: Methods and Applications of Statistics in Business, Finance, and Management Science Narayanaswamy Balakrishnan, 2010-07-13 Inspired by the Encyclopedia of Statistical Sciences, Second Edition, this volume presents the tools and techniques that are essential for carrying out best practices in the modern business world The collection and analysis of quantitative data drives some of the most important conclusions that are drawn in today's business world, such as the preferences of a customer base, the quality of manufactured products, the marketing of products, and the availability of financial resources. As a result, it is essential for individuals working in this environment to have the knowledge and skills to interpret and use statistical techniques in various scenarios. Addressing this need, Methods and Applications of Statistics in Business, Finance, and Management Science serves as a single, one-of-a-kind resource that guides readers through the use of common statistical practices by presenting real-world applications from the fields of business, economics, finance, operations research, and management science. Uniting established literature with the latest research, this volume features classic articles from the acclaimed Encyclopedia of Statistical Sciences, Second Edition along with brand-new contributions written by today's leading academics and practitioners. The result is a compilation that explores classic methodology and new topics, including: Analytical methods for risk management Statistical modeling for online auctions Ranking and selection in mutual funds Uses of Black-Scholes formula in finance Data mining in prediction markets From auditing and marketing to stock market price indices and banking, the presented literature sheds light on the use of quantitative methods in research relating to common financial applications. In addition, the book supplies insight on common uses of statistical techniques such as Bayesian methods, optimization, simulation, forecasting, mathematical modeling, financial time series, and data mining in modern research. Providing a blend of traditional methodology and the latest research, Methods and Applications of Statistics in Business, Finance, and Management Science is an excellent reference for researchers, managers, consultants, and students in the fields of business, management science, operations research, supply chain management, mathematical finance, and economics who must understand statistical literature and carry out quantitative practices to make smart business decisions in their everyday work. |
| modern spectrum analysis of time series: Fast NMR Data Acquisition Mehdi Mobli, Jeffrey C Hoch, 2017-05-18 Providing a definitive reference source on novel methods in NMR acquisition and processing, this book will highlight similarities and differences between emerging approaches and focus on identifying which methods are best suited for different applications. The highly qualified editors have conducted extensive research into the fundamentals of fast methods of data acquisition in NMR, including applications of non-Fourier methods of spectrum analysis. With contributions from additional distinguished experts in allied fields, clear explanations are provided on methods that speed up NMR experiments using different ways to manipulate the nuclei in the sample, modern methods for estimating the spectrum from the time domain response recorded during an NMR experiment, and finally how the data is sampled. Starting with a historical overview of Fourier Transformation and its role in modern NMR spectroscopy, this volume will clarify and demystify this important emerging field for spectroscopists and analytical chemists in industry and academia. |
| modern spectrum analysis of time series: Automatic Autocorrelation and Spectral Analysis Piet M. T. Broersen, 2006-04-20 Automatic Autocorrelation and Spectral Analysis gives random data a language to communicate the information they contain objectively. It takes advantage of greater computing power and robust algorithms to produce enough candidate models of a given group of data to be sure of providing a suitable one. Improved order selection guarantees that one of the best (often the best) will be selected automatically. Written for graduate signal processing students and for researchers and engineers using time series analysis for applications ranging from breakdown prevention in heavy machinery to measuring lung noise for medical diagnosis, this text offers: - tuition in how power spectral density and the autocorrelation function of stochastic data can be estimated and interpreted in time series models; - extensive support for the MATLAB® ARMAsel toolbox; - applications showing the methods in action; - appropriate mathematics for students to apply the methods with references for those who wish to develop them further. |
| modern spectrum analysis of time series: Data Analysis Methods in Physical Oceanography William J. Emery, Richard E. Thomson, 2001-04-03 Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:. An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.. A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.. 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: (...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers. Aslib Book Guide Vol 63, No. 9, 1998 (...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching. EOS Transactions, D.A. Jay, 1999 (...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations. Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 (...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries. E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999 |
| modern spectrum analysis of time series: Spectral Analysis in Geophysics B.M. Båth, 2012-12-02 Spectral Analysis in Geophysics |
| modern spectrum analysis of time series: Encyclopedia of Quaternary Science , 2006-11-24 The quaternary sciences constitute a dynamic, multidisciplinary field of research that has been growing in scientific and societal importance in recent years. This branch of the Earth sciences links ancient prehistory to modern environments. Quaternary terrestrial sediments contain the fossil remains of existing species of flora and fauna, and their immediate predecessors. Quaternary science plays an integral part in such important issues for modern society as groundwater resources and contamination, sea level change, geologic hazards (earthquakes, volcanic eruptions, tsunamis), and soil erosion. With over 360 articles and 2,600 pages, many in full-color, the Encyclopedia of Quaternary Science provides broad ranging, up-to-date articles on all of the major topics in the field. Written by a team of leading experts and under the guidance of an international editorial board, the articles are at a level that allows undergraduate students to understand the material, while providing active researchers with the latest information in the field. Also available online via ScienceDirect (2006) – featuring extensive browsing, searching, and internal cross-referencing between articles in the work, plus dynamic linking to journal articles and abstract databases, making navigation flexible and easy. For more information, pricing options and availability visit www.info.sciencedirect.com. 360 individual articles written by prominent international authorities, encompassing all important aspects of quaternary science Each entry provides comprehensive, in-depth treatment of an overview topic and presented in a functional, clear and uniform layout Reference section provides guidence for further research on the topic Article text supported by full-color photos, drawings, tables, and other visual material Writing level is suited to both the expert and non-expert |
| modern spectrum analysis of time series: Paleontological Data Analysis Øyvind Hammer, David A. T. Harper, 2024-06-04 PALEONTOLOGICAL DATA ANALYSIS An up-to-date edition of the indispensable guide to analysing paleontological data Paleontology has developed in recent decades into an increasingly data-driven discipline, which brings to bear a huge variety of statistical tools. Applying statistical methods to paleontological data requires a discipline-specific understanding of which methods and parameters are the most appropriate ones, and how to account for statistical bias inherent in the fossil record. By guiding the reader to these and other fundamental questions in the statistical analysis of fossilized specimens, Paleontological Data Analysis has become the standard text for anyone with an interest in quantitative analysis of the fossil record. Now fully updated to reflect the latest statistical methods and disciplinary advances, it is an essential tool for practitioners and students alike. Readers of the second edition of Paleontological Data Analysis readers will also find: New sections on machine learning, Bayesian inference, phylogenetic comparative methods, analysis of CT data, and much more New use cases and examples using PAST, R, and Python software packages Full color illustrations throughout Paleontological Data Analysis is ideal for paleontologists, evolutionary biologists, taxonomists, and students in any of these fields. |
| modern spectrum analysis of time series: Introduction to Applied Statistical Signal Analysis Richard Shiavi, 2010-07-19 Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain. |
| modern spectrum analysis of time series: Maximum Entropy and Bayesian Methods John Skilling, 2013-06-29 Cambridge, England, 1988 |
| modern spectrum analysis of time series: Nonlinear Time Series Analysis Holger Kantz, Thomas Schreiber, 2004 The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences. |
| modern spectrum analysis of time series: Optimum Array Processing Harry L. Van Trees, 2002-04-04 Array Processing ist eine wichtige Anwendung im Bereich der digitalen Signalverarbeitung. Eingesetzt wird sie u.a. in der Radar-, Sonar- und Kommuniktionstechnik, in der Seismologie und der Biomedizintechnik. Van Trees zweibändiges Werk 'Detection Estimation and Modulation Theory', das 1972 vom Wiley College Department herausgegeben wurde, war damals ein echter Klassiker. Array Processing: Detection and Estimation Theory ist das aktuellste und umfassendste Buch zu diesem Thema. Auf 1.400 Seiten wird die Array Signalverarbeitung umfassend und enzyklopädisch erläutert. Dabei werden auch alle modernen Anwendungen, von der Biomedizin bis hin zur drahtlosen Kommunikation berücksichtigt. Jedes Kapitel enthält eine Zusammenfassung, Beispiele und zahlreiche Problemstellungen. Der Stoff ist übersichtlich gegliedert und wird anschaulich und verständlich vermittelt. Array Processing: Detection and Estimation Theory ist ein topaktuelles Nachschlagewerk im Doppelpack: Zum Buch gehört die nachgedruckte Broschurausgabe des zweibändigen Vorgängertitels, der eine ideale Einführung in die komplexe Theorie bietet, die im aktuellen Band behandelt wird. |
| modern spectrum analysis of time series: Modern Spectral Estimation Steven M. Kay, 1988 |
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MODERN Definition & Meaning - Merriam-Webster
The meaning of MODERN is of, relating to, or characteristic of the present or the immediate past : contemporary. How to use modern in a sentence.
MODERN | English meaning - Cambridge Dictionary
MODERN definition: 1. designed and made using the most recent ideas and methods: 2. of the present or recent times…. Learn more.
Modern - Wikipedia
Modernity, a loosely defined concept delineating a number of societal, economic and ideological features that contrast with "pre-modern" times or societies Late modernity Art
Modern - definition of modern by The Free Dictionary
Characteristic or expressive of recent times or the present; contemporary or up-to-date: a modern lifestyle; a modern way of thinking. 2. a. Of or relating to a recently developed or advanced …
MODERN definition and meaning | Collins English Dictionary
modern is applied to those things that exist in the present age, esp. in contrast to those of a former age or an age long past; hence the word sometimes has the connotation of up-to-date …
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What does modern mean? - Definitions.net
Modern typically refers to the present or recent times as opposed to the past. It commonly relates to developments or characteristics regarded as representative of contemporary life, or the …
MODERN Definition & Meaning | Dictionary.com
Modern means relating to the present time, as in modern life. It also means up-to-date and not old, as in modern technology. Apart from these general senses, modern is often used in a …
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Modern definition: Of, relating to, or being a living language or group of languages.
Modern Optical
At Modern Optical, we believe all families deserve fashionable, affordable eyewear. Founded in 1974 by my father, Yale Weissman, Modern remains family-owned and operated as well as a …
MODERN Definition & Meaning - Merriam-Webster
The meaning of MODERN is of, relating to, or characteristic of the present or the immediate past : contemporary. How to use modern in a sentence.
MODERN | English meaning - Cambridge Dictionary
MODERN definition: 1. designed and made using the most recent ideas and methods: 2. of the present or recent times…. Learn more.
Modern - Wikipedia
Modernity, a loosely defined concept delineating a number of societal, economic and ideological features that contrast with "pre-modern" times or societies Late modernity Art
Modern - definition of modern by The Free Dictionary
Characteristic or expressive of recent times or the present; contemporary or up-to-date: a modern lifestyle; a modern way of thinking. 2. a. Of or relating to a recently developed or advanced …
MODERN definition and meaning | Collins English Dictionary
modern is applied to those things that exist in the present age, esp. in contrast to those of a former age or an age long past; hence the word sometimes has the connotation of up-to-date …
Modern Muse Salon | Collierville TN - Facebook
Modern Muse Salon, Collierville, TN. 434 likes · 31 talking about this · 99 were here. Luxury hair salon located in Collierville at the corner of Poplar & Houston Levee!
What does modern mean? - Definitions.net
Modern typically refers to the present or recent times as opposed to the past. It commonly relates to developments or characteristics regarded as representative of contemporary life, or the …
MODERN Definition & Meaning | Dictionary.com
Modern means relating to the present time, as in modern life. It also means up-to-date and not old, as in modern technology. Apart from these general senses, modern is often used in a …
Modern Definition & Meaning - YourDictionary
Modern definition: Of, relating to, or being a living language or group of languages.
