Author : Chun-Kit Ngan
Publisher : BoD – Books on Demand
Release Date : 2019-11-06
ISBN 10 : 9781789847789
Pages : 130 pages
File Format : PDF, EPUB, TEXT, KINDLE or MOBI
Rating : 4.4/5 (847 users download)
Download Time Series Analysis by Chun-Kit Ngan PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis by Chun-Kit Ngan. This book is available in ePub and PDF format with a single click unlimited downloads. This book aims to provide readers with the current information, developments, and trends in a time series analysis, particularly in time series data patterns, technical methodologies, and real-world applications. This book is divided into three sections and each section includes two chapters. Section 1 discusses analyzing multivariate and fuzzy time series. Section 2 focuses on developing deep neural networks for time series forecasting and classification. Section 3 describes solving real-world domain-specific problems using time series techniques. The concepts and techniques contained in this book cover topics in time series research that will be of interest to students, researchers, practitioners, and professors in time series forecasting and classification, data analytics, machine learning, deep learning, and artificial intelligence.
Download Practical Time Series Analysis by Aileen Nielsen PDF/Ebook Free clicking on the below button will initiate the downloading process of Practical Time Series Analysis by Aileen Nielsen. This book is available in ePub and PDF format with a single click unlimited downloads. Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
Download Macroeconometrics and Time Series Analysis by Steven Durlauf PDF/Ebook Free clicking on the below button will initiate the downloading process of Macroeconometrics and Time Series Analysis by Steven Durlauf. This book is available in ePub and PDF format with a single click unlimited downloads. Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Download Time Series Analysis and Adjustment by Haim Y Bleikh PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis and Adjustment by Haim Y Bleikh. This book is available in ePub and PDF format with a single click unlimited downloads. In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.
Download Time Series Analysis in Seismology by Alejandro Ramírez-Rojas PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis in Seismology by Alejandro Ramírez-Rojas. This book is available in ePub and PDF format with a single click unlimited downloads. Time Series Analysis in Seismology: Practical Applications provides technical assistance and coverage of available methods to professionals working in the field of seismology. Beginning with a thorough review of open problems in geophysics, including tectonic plate dynamics, localization of solitons, and forecasting, the book goes on to describe the various types of time series or punctual processes obtained from those systems. Additionally, the book describes a variety of methods and techniques relating to seismology and includes a discussion of future developments and improvements. Time Series Analysis in Seismology offers a concise presentation of the most recent advances in the analysis of geophysical data, particularly with regard to seismology, making it a valuable tool for researchers and students working in seismology and geophysics. Presents the necessary tools for time series analysis as it relates to seismology in a compact and consistent manner Includes a discussion of technical resources that can be applied to time series data analysis across multiple disciplines Describes the methods and techniques available for solving problems related to the analysis of complex data sets Provides exercises at the end of each chapter to enhance comprehension
Download Robust and Nonlinear Time Series Analysis by J. Franke PDF/Ebook Free clicking on the below button will initiate the downloading process of Robust and Nonlinear Time Series Analysis by J. Franke. This book is available in ePub and PDF format with a single click unlimited downloads. Classical time series methods are based on the assumption that a particular stochastic process model generates the observed data. The, most commonly used assumption is that the data is a realization of a stationary Gaussian process. However, since the Gaussian assumption is a fairly stringent one, this assumption is frequently replaced by the weaker assumption that the process is wide~sense stationary and that only the mean and covariance sequence is specified. This approach of specifying the probabilistic behavior only up to "second order" has of course been extremely popular from a theoretical point of view be cause it has allowed one to treat a large variety of problems, such as prediction, filtering and smoothing, using the geometry of Hilbert spaces. While the literature abounds with a variety of optimal estimation results based on either the Gaussian assumption or the specification of second-order properties, time series workers have not always believed in the literal truth of either the Gaussian or second-order specifica tion. They have none-the-less stressed the importance of such optimali ty results, probably for two main reasons: First, the results come from a rich and very workable theory. Second, the researchers often relied on a vague belief in a kind of continuity principle according to which the results of time series inference would change only a small amount if the actual model deviated only a small amount from the assum ed model.
Download Time Series Analysis and Applications to Geophysical Systems by David Brillinger PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis and Applications to Geophysical Systems by David Brillinger. This book is available in ePub and PDF format with a single click unlimited downloads. This IMA Volume in Mathematics and its Applications TIME SERIES ANALYSIS AND APPLICATIONS TO GEOPHYSICAL SYSTEMS contains papers presented at a very successful workshop on the same title. The event which was held on November 12-15, 2001 was an integral part of the IMA 2001-2002 annual program on " Mathematics in the Geosciences. " We would like to thank David R. Brillinger (Department of Statistics, Uni versity of California, Berkeley), Enders Anthony Robinson (Department of Earth and Environmental Engineering, Columbia University), and Fred eric Paik Schoenberg (Department of Statistics, University of California, Los Angeles) for their superb role as workshop organizers and editors of the proceedings. We are also grateful to Robert H. Shumway (Department of Statistics, University of California, Davis) for his help in organizing the four-day event. We take this opportunity to thank the National Science Foundation for its support of the IMA. Series Editors Douglas N. Arnold, Director of the IMA Fadil Santosa, Deputy Director of the IMA v PREFACE This volume contains a collection of papers that were presented dur ing the Workshop on Time Series Analysis and Applications to Geophysical Systems at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota from November 12-15, 2001. This was part of the IMA Thematic Year on Mathematics in the Geosciences, and was the last in a series of four Workshops during the Fall Quarter dedicated to Dynamical Systems and Ergodic Theory.
Download Time Series Analysis and Its Applications by Robert H. Shumway PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis and Its Applications by Robert H. Shumway. This book is available in ePub and PDF format with a single click unlimited downloads. Geared to people involved in statistics, medicine, engineering, and economics, this book offers a basic introduction to time series analysis, providing a balanced and comprehensive treatment of time and frequency domain methods, with accompanying theory. Examples throughout deal with practical, real-world situations.
Download Time Series Analysis with Long Memory in View by Uwe Hassler PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis with Long Memory in View by Uwe Hassler. This book is available in ePub and PDF format with a single click unlimited downloads. Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests. Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book: Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs Contains many new results on long memory processes which have not appeared in previous and existing textbooks Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory Contains 25 illustrative figures as well as lists of notations and acronyms Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.
Download Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance by Michael Small PDF/Ebook Free clicking on the below button will initiate the downloading process of Applied Nonlinear Time Series Analysis: Applications in Physics, Physiology and Finance by Michael Small. This book is available in ePub and PDF format with a single click unlimited downloads. Nonlinear time series methods have developed rapidly over a quarter of a century and have reached an advanced state of maturity during the last decade. Implementations of these methods for experimental data are now widely accepted and fairly routine; however, genuinely useful applications remain rare. This book focuses on the practice of applying these methods to solve real problems. To illustrate the usefulness of these methods, a wide variety of physical and physiological systems are considered. The technical tools utilized in this book fall into three distinct, but interconnected areas: quantitative measures of nonlinear dynamics, Monte-Carlo statistical hypothesis testing, and nonlinear modeling. Ten highly detailed applications serve as case studies of fruitful applications and illustrate the mathematical techniques described in the text. Contents:Times Series Embedding and ReconstructionDynamics Measures and Topological InvariantsEstimation of Correlation DimensionThe Method of Surrogate DataNon-Standard and Nonlinear SurrogatesIdentifying the DynamicsApplications Readership: Postgraduate students, researchers, academics and practitioners in nonlinear physics and in various other areas of potential application (e.g. engineering, biology and medicine). Keywords:Deterministic Nonlinear Dynamics;Nonlinear Time Series Analysis;Chaos;Dynamical Systems;Computational Modeling;Simulation and Prediction;Correlation Dimension;Surrogate Time Series MethodsKey Features:Despite standard nonlinear modeling methods (neural networks, radial basis functions and so on) being the subject of numerous excellent texts, this book focuses on finding the best model and how to determine when a given model is “good enough”Several new, state-of-the-art methods to circumvent the problems of standard methods are described and demonstrated to have useful applicationsSurrogate data methods are extended beyond the linear domain to provide useful tests of several classes of nonlinear systems
Download Time Series Analysis by Oliver Duncan Anderson PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis by Oliver Duncan Anderson. This book is available in ePub and PDF format with a single click unlimited downloads.
Download Market Response Models by Dominique M. Hanssens PDF/Ebook Free clicking on the below button will initiate the downloading process of Market Response Models by Dominique M. Hanssens. This book is available in ePub and PDF format with a single click unlimited downloads. From 1976 to the beginning of the millennium—covering the quarter-century life span of this book and its predecessor—something remarkable has happened to market response research: it has become practice. Academics who teach in professional fields, like we do, dream of such things. Imagine the satisfaction of knowing that your work has been incorporated into the decision-making routine of brand managers, that category management relies on techniques you developed, that marketing management believes in something you struggled to establish in their minds. It’s not just us that we are talking about. This pride must be shared by all of the researchers who pioneered the simple concept that the determinants of sales could be found if someone just looked for them. Of course, economists had always studied demand. But the project of extending demand analysis would fall to marketing researchers, now called marketing scientists for good reason, who saw that in reality the marketing mix was more than price; it was advertising, sales force effort, distribution, promotion, and every other decision variable that potentially affected sales. The bibliography of this book supports the notion that the academic research in marketing led the way. The journey was difficult, sometimes halting, but ultimately market response research advanced and then insinuated itself into the fabric of modern management.
Download Time Series Analysis by State Space Methods by The late James Durbin PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis by State Space Methods by The late James Durbin. This book is available in ePub and PDF format with a single click unlimited downloads. This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis providing a more comprehensive treatment, including the filtering of nonlinear and non-Gaussian series. The book provides an excellent source for the development of practical courses on time series analysis.
Download Time Series Analysis by Oliver D. Anderson PDF/Ebook Free clicking on the below button will initiate the downloading process of Time Series Analysis by Oliver D. Anderson. This book is available in ePub and PDF format with a single click unlimited downloads.
Download Applications of Time Series Analysis in Astronomy and Meteorology by T. Subba Rao PDF/Ebook Free clicking on the below button will initiate the downloading process of Applications of Time Series Analysis in Astronomy and Meteorology by T. Subba Rao. This book is available in ePub and PDF format with a single click unlimited downloads. Very Good,No Highlights or Markup,all pages are intact.
Download Linear Models for Multivariate, Time Series, and Spatial Data by Ronald Christensen PDF/Ebook Free clicking on the below button will initiate the downloading process of Linear Models for Multivariate, Time Series, and Spatial Data by Ronald Christensen. This book is available in ePub and PDF format with a single click unlimited downloads. A companion volume to Plane answers to complex questions: the theory of linear models (1987), presenting six chapters with shallow treatments of very broad topics showing how the properties of three fundamental ideas from standard linear model theory can be used to examine multivariate, time series,
Download Pooled Time Series Analysis by Lois W. Sayrs PDF/Ebook Free clicking on the below button will initiate the downloading process of Pooled Time Series Analysis by Lois W. Sayrs. This book is available in ePub and PDF format with a single click unlimited downloads. Combining time series and cross-sectional data provides the researcher with an efficient method of analysis and improved estimates of the population being studied. This analysis technique allows the sample size to be increased, which ultimately yields a more effective study.