January 25, 2021

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Applied Time Series Analysis

Applied Time Series Analysis
Author : Terence C. Mills
Publisher : Academic Press
Release Date : 2019-02-08
Category : Business & Economics
Total pages :432
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Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others. Focuses on practical application of time series analysis, using step-by-step techniques and without excessive technical detail Supported by copious disciplinary examples, helping readers quickly adapt time series analysis to their area of study Covers both univariate and multivariate techniques in one volume Provides expert tips on, and helps mitigate common pitfalls of, powerful statistical software including EVIEWS and R Written in jargon-free and clear English from a master educator with 30 years+ experience explaining time series to novices Accompanied by a microsite with disciplinary data sets and files explaining how to build the calculations used in examples

Applied Time Series Analysis with R

Applied Time Series Analysis with R
Author : Wayne A. Woodward,Henry L. Gray,Alan C. Elliott
Publisher : CRC Press
Release Date : 2017-02-17
Category : Mathematics
Total pages :618
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Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis. Features Gives readers the ability to actually solve significant real-world problems Addresses many types of nonstationary time series and cutting-edge methodologies Promotes understanding of the data and associated models rather than viewing it as the output of a "black box" Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website. Over 150 exercises and extensive support for instructors The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with time-varying frequencies (TVF).

Applied Time Series

Applied Time Series
Author : T. M. J. A. Cooray
Publisher : Unknown
Release Date : 2008
Category : Mathematics
Total pages :280
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Applied Time Series: Analysis and Forecasting provides the theories, methods and tools for necessary modeling and forecasting of time series. It includes a complete theoretical development of univariate time series models with each step demonstrated with an analysis of real time data series. The result is clear presentation, quantified subjective judgment derived from selected methods applied to time series observations.

Applied Time Series Econometrics

Applied Time Series Econometrics
Author : Helmut Lütkepohl,Markus Krätzig
Publisher : Cambridge University Press
Release Date : 2004-08-04
Category : Business & Economics
Total pages :323
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A demonstration of how time series econometrics can be used in economics and finance.

Applied Statistical Time Series Analysis

Applied Statistical Time Series Analysis
Author : Robert H. Shumway
Publisher : Prentice Hall
Release Date : 1988
Category : Mathematics
Total pages :379
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Applied Bayesian Forecasting and Time Series Analysis

Applied Bayesian Forecasting and Time Series Analysis
Author : Andy Pole,Mike West,Jeff Harrison
Publisher : CRC Press
Release Date : 2018-10-08
Category : Business & Economics
Total pages :432
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Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for forecasting and the analysis of time series. The authors unify the concepts, model forms, and modeling requirements within the framework of the dynamic linear mode (DLM). They include a complete theoretical development of the DLM and illustrate each step with analysis of time series data. Using real data sets the authors: Explore diverse aspects of time series, including how to identify, structure, explain observed behavior, model structures and behaviors, and interpret analyses to make informed forecasts Illustrate concepts such as component decomposition, fundamental model forms including trends and cycles, and practical modeling requirements for routine change and unusual events Conduct all analyses in the BATS computer programs, furnishing online that program and the more than 50 data sets used in the text The result is a clear presentation of the Bayesian paradigm: quantified subjective judgements derived from selected models applied to time series observations. Accessible to undergraduates, this unique volume also offers complete guidelines valuable to researchers, practitioners, and advanced students in statistics, operations research, and engineering.

APPLIED TIME SERIES ANALYSIS FOR MANAGERIAL FORECASTING

APPLIED TIME SERIES ANALYSIS FOR MANAGERIAL FORECASTING
Author : CHARLES R. NELSON
Publisher : Unknown
Release Date : 2021
Category :
Total pages :129
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Time Series Analysis and Its Applications

Time Series Analysis and Its Applications
Author : Robert H. Shumway,David S. Stoffer
Publisher : Unknown
Release Date : 2014-01-15
Category :
Total pages :568
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Time Series Analysis

Time Series Analysis
Author : Jonathan D. Cryer,Kung-Sik Chan
Publisher : Springer Science & Business Media
Release Date : 2008-04-04
Category : Business & Economics
Total pages :491
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This book presents an accessible approach to understanding time series models and their applications. The ideas and methods are illustrated with both real and simulated data sets. A unique feature of this edition is its integration with the R computing environment.

Time Series Analysis

Time Series Analysis
Author : Henrik Madsen
Publisher : CRC Press
Release Date : 2007-11-28
Category : Mathematics
Total pages :400
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With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the author presents theorems to highlight the most important results, proofs to clarify some results, and problems to illustrate the use of the results for modeling real-life phenomena. The book first provides the formulas and methods needed to adapt a second-order approach for characterizing random variables as well as introduces regression methods and models, including the general linear model. It subsequently covers linear dynamic deterministic systems, stochastic processes, time domain methods where the autocorrelation function is key to identification, spectral analysis, transfer-function models, and the multivariate linear process. The text also describes state space models and recursive and adaptivemethods. The final chapter examines a host of practical problems, including the predictions of wind power production and the consumption of medicine, a scheduling system for oil delivery, and the adaptive modeling of interest rates. Concentrating on the linear aspect of this subject, Time Series Analysis provides an accessible yet thorough introduction to the methods for modeling linear stochastic systems. It will help you understand the relationship between linear dynamic systems and linear stochastic processes.

Applied Time Series Analysis of Economic Data

Applied Time Series Analysis of Economic Data
Author : Conference on Applied Time Series Analysis of Economic Data
Publisher : Unknown
Release Date : 1983
Category :
Total pages :399
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Applied Time Series Analysis

Applied Time Series Analysis
Author : Anonim
Publisher : Unknown
Release Date : 1997
Category :
Total pages :129
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Introduction to Time Series Analysis

Introduction to Time Series Analysis
Author : Mark Pickup
Publisher : SAGE Publications
Release Date : 2014-10-15
Category : Social Science
Total pages :232
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Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University

Applied Time Series Analysis II

Applied Time Series Analysis II
Author : David F. Findley
Publisher : Academic Press
Release Date : 2014-05-10
Category : Mathematics
Total pages :810
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Applied Time Series Analysis II contains the proceedings of the Second Applied Time Series Symposium Held in Tulsa, Oklahoma, on March 3-5, 1980. The symposium provided a forum for discussing significant advances in time series analysis and signal processing. Effective alternatives to the familiar least-square and maximum likelihood procedures are described, along with maximum likelihood procedures for modeling irregularly sampled series and for classifying non-stationary series. Comprised of 22 chapters, this volume begins with an introduction to the multidimensional filtering theory and presents specific case histories related to the multidimensional recursive filter stability problem; the least squares inverse problem; realization of filters; and spectral estimation. The unique properties of the three-dimensional wave equation are also considered. Subsequent chapters focus on high-resolution spectral estimators; time series analysis of geophysical inverse scattering problems; minimum entropy deconvolution; and fitting of a continuous time autoregression to discrete data. This monograph will appeal to students and practitioners in the fields of mathematics and statistics, electrical and electronics engineering, and information and computer sciences.

Applied Time Series Analysis

Applied Time Series Analysis
Author : Moguens Bladt
Publisher : Unknown
Release Date : 1995
Category : Time-series analysis
Total pages :91
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