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Applied Time Series Analysis

Applied Time Series Analysis
  • Author : Terence C. Mills
  • Publsiher : Academic Press
  • Release : 08 February 2019
  • ISBN : 0128131179
  • Pages : 432 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKApplied Time Series Analysis

Summary:
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

Applied Time Series Analysis
  • Author : Terence C. Mills
  • Publisher : Academic Press
  • Release : 08 February 2019
GET THIS BOOKApplied Time Series Analysis

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


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 : 17 February 2017
GET THIS BOOKApplied Time Series Analysis with R

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


Applied Time Series

Applied Time Series
  • Author : T. M. J. A. Cooray
  • Publisher : Anonim
  • Release : 27 February 2021
GET THIS BOOKApplied Time Series

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 Bayesian Forecasting and Time Series Analysis

Applied Bayesian Forecasting and Time Series Analysis
  • Author : Andy Pole,Mike West,Jeff Harrison
  • Publisher : CRC Press
  • Release : 08 October 2018
GET THIS BOOKApplied Bayesian Forecasting and Time Series Analysis

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,


Applied Time Series Analysis II

Applied Time Series Analysis II
  • Author : David F. Findley
  • Publisher : Academic Press
  • Release : 10 May 2014
GET THIS BOOKApplied Time Series Analysis II

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


Applied Time Series Analysis and Innovative Computing

Applied Time Series Analysis and Innovative Computing
  • Author : Sio-Iong Ao
  • Publisher : Springer Science & Business Media
  • Release : 21 April 2010
GET THIS BOOKApplied Time Series Analysis and Innovative Computing

Applied Time Series Analysis and Innovative Computing contains the applied time series analysis and innovative computing paradigms, with frontier application studies for the time series problems based on the recent works at the Oxford University Computing Laboratory, University of Oxford, the University of Hong Kong, and the Chinese University of Hong Kong. The monograph was drafted when the author was a post-doctoral fellow in Harvard School of Engineering and Applied Sciences, Harvard University. It provides a systematic introduction to the






Time Series

Time Series
  • Author : Robert Shumway,David Stoffer
  • Publisher : CRC Press
  • Release : 17 May 2019
GET THIS BOOKTime Series

The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. A useful feature of the presentation is the inclusion of nontrivial data sets illustrating the richness of potential applications to problems in the biological, physical, and social sciences as well as medicine. The text presents a balanced and comprehensive treatment of both time and frequency domain methods with an emphasis


Time Series Analysis

Time Series Analysis
  • Author : Henrik Madsen
  • Publisher : CRC Press
  • Release : 28 November 2007
GET THIS BOOKTime Series Analysis

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



Applied Time Series Analysis

Applied Time Series Analysis
  • Author : C. Planas
  • Publisher : Anonim
  • Release : 01 January 1997
GET THIS BOOKApplied Time Series Analysis

"The general purpose of this textbook is to provide analysts in statistical institutes with a unified view of applied analysis of time series as can be conducted in the framework of linear stochastic models of the ARIMA-type. The issues discussed are modelling and forecasting, filtering, signal extraction and unobserved components analysis, and regression in time series models. The main concern is to help readers in understanding some important tools that progress in statistical theory has made available. Emphasis is thus