Applied Time Series
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Applied Time Series Analysis
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Author : Terence C. Mills
language : en
Publisher: Academic Press
Release Date : 2019-02-08
Applied Time Series Analysis written by Terence C. Mills and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-08 with Business & Economics categories.
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
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Author : Wayne A. Woodward
language : en
Publisher: CRC Press
Release Date : 2017-02-17
Applied Time Series Analysis With R written by Wayne A. Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Mathematics categories.
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 Analysis And Forecasting With Python
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Author : Changquan Huang
language : en
Publisher: Springer Nature
Release Date : 2022-10-19
Applied Time Series Analysis And Forecasting With Python written by Changquan Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-19 with Mathematics categories.
This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement them and solve data science problems. It covers not only common statistical approaches and time series models, including ARMA, SARIMA, VAR, GARCH and state space and Markov switching models for (non)stationary, multivariate and financial time series, but also modern machine learning procedures and challenges for time series forecasting. Providing an organic combination of the principles of time series analysis and Python programming, it enables the reader to study methods and techniques and practice writing and running Python code at the same time. Its data-driven approach to analyzing and modeling time series data helps new learners to visualize and interpret both the raw data and its computed results. Primarily intended for students of statistics, economics and data science with an undergraduate knowledge of probability and statistics, the book will equally appeal to industry professionals in the fields of artificial intelligence and data science, and anyone interested in using Python to solve time series problems.
Applied Time Series Analysis For The Social Sciences
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Author : Richard McCleary
language : en
Publisher: SAGE Publications, Incorporated
Release Date : 1980-07
Applied Time Series Analysis For The Social Sciences written by Richard McCleary and has been published by SAGE Publications, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980-07 with Mathematics categories.
McCleary and Hay have made time series analysis techniques -- the Box-Jenkins or ARIMA methods -- accessible to the social scientist. Rejecting the dictum that time series analysis requires substantial mathematical sophistication, the authors take a clearly written, step-by-step approach. They describe the logic behind time series analysis, and its possible applications in impact assessment, causal modelling and forecasting, multivariate time series and parameter estimation.
Applied Time Series
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Author : T. M. J. A. Cooray
language : en
Publisher:
Release Date :
Applied Time Series written by T. M. J. A. Cooray and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Applied Time Series Analysis Basic Techniques
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Author : Robert K. Otnes
language : en
Publisher: John Wiley & Sons
Release Date : 1978
Applied Time Series Analysis Basic Techniques written by Robert K. Otnes and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Business & Economics categories.
Preliminary concepts; Probability and statistical concepts; Collecting and preprocessing data; Design of digital filters; Practical aspects of digital filtering; Fourier transforms; Covariance and convolution functions; Power and cross spectral densities; Transfer functions and coherence function; Computer subroutines for time series analysis.
Time Series Analysis And Its Applications
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Author : Robert H. Shumway
language : en
Publisher: Springer
Release Date : 2017-04-25
Time Series Analysis And Its Applications written by Robert H. Shumway and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-25 with Mathematics categories.
The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.
Applied Time Series Analysis For Managerial Forecasting
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Author : Charles R. Nelson
language : en
Publisher:
Release Date : 1973
Applied Time Series Analysis For Managerial Forecasting written by Charles R. Nelson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with Business forecasting categories.
Applied Time Series Econometrics
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Author : Helmut Lütkepohl
language : en
Publisher: Cambridge University Press
Release Date : 2004-08-02
Applied Time Series Econometrics written by Helmut Lütkepohl and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-02 with Business & Economics categories.
Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
Applied Time Series And Box Jenkins Models
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Author : Walter Vandaele
language : en
Publisher:
Release Date : 1983
Applied Time Series And Box Jenkins Models written by Walter Vandaele and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Business & Economics categories.
This text presents Time Series analysis and Box-Jenkins models.