Download or read book Applied Time Series and Box Jenkins Models written by Walter Vandaele and published by . This book was released on 1983 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents Time Series analysis and Box-Jenkins models.
Download or read book Time Series Analysis Forecasting Control 3 E written by and published by Pearson Education India. This book was released on 1994-09 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a complete revision of a classic, seminal, and authoritative text that has been the model for most books on the topic written since 1970. It explores the building of stochastic (statistical) models for time series and their use in important areas of application -forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.
Download or read book Time Series Analysis written by George E. P. Box and published by . This book was released on 1976 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction and summary; Stochastic models and their forecasting; The autocorrelation function and spectrum; Linear stationary models; Linear nonstationary models; Forecasting; Stochastic model building; Model identification; Model estimation; Model diagnostic checking; Seasonal models; Transfer function models; Identification fitting, and checking of transfer function models.
Download or read book Applied Time Series Analysis for the Social Sciences written by Richard McCleary and published by SAGE Publications, Incorporated. This book was released on 1980-07 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applied Time Series Analysis written by Terence C. Mills and published by Academic Press. This book was released on 2019-02-08 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Forecasting with Univariate Box Jenkins Models written by Alan Pankratz and published by John Wiley & Sons, Incorporated. This book was released on 1983-08-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.
Download or read book Forecasting with Univariate Box Jenkins Models written by Alan Pankratz and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.
Download or read book Essentials of Time Series for Financial Applications written by Massimo Guidolin and published by Academic Press. This book was released on 2018-05-29 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. Provides practical, hands-on examples in time-series econometrics Presents a more application-oriented, less technical book on financial econometrics Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction Features examples worked out in EViews (9 or higher)
Download or read book Time Series and Forecasting written by Bruce L. Bowerman and published by Brooks/Cole. This book was released on 1979 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting and multiple regression analysis; Forecasting time series described by trend and irregular components; Forecasting seasonal time series; The box-jenkins methodology.
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series Analysis and Forecasting written by Lon-Mu Liu and published by . This book was released on 2006-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Practical Time Series Analysis written by Aileen Nielsen and published by O'Reilly Media. This book was released on 2019-09-20 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 or read book Time Series Analysis for the Social Sciences written by Janet M. Box-Steffensmeier and published by Cambridge University Press. This book was released on 2014-12-22 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.
Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
Download or read book Interrupted Time Series Analysis written by David McDowall and published by Oxford University Press, USA. This book was released on 2019 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It provides example analyses of social, behavioral, and biomedical time series to illustrate a general strategy for building AutoRegressive Integrated Moving Average (ARIMA) impact models. Additionally, the book supplements the classic Box-Jenkins-Tiao model-building strategy with recent auxiliary tests for transformation, differencing, and model selection. Not only does the text discuss new developments, including the prospects for widespread adoption of Bayesian hypothesis testing and synthetic control group designs, but it makes optimal use of graphical illustrations in its examples. With forty completed example analyses that demonstrate the implications of model properties, Interrupted Time Series Analysis will be a key inter-disciplinary text in classrooms, workshops, and short-courses for researchers familiar with time series data or cross-sectional regression analysis but limited background in the structure of time series processes and experiments.
Download or read book Time Series Analysis and Forecasting by Example written by Søren Bisgaard and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in detail and explain the relevant theory while also focusing on the interpretation of results in data analysis. Following a discussion of why autocorrelation is often observed when data is collected in time, subsequent chapters explore related topics, including: Graphical tools in time series analysis Procedures for developing stationary, non-stationary, and seasonal models How to choose the best time series model Constant term and cancellation of terms in ARIMA models Forecasting using transfer function-noise models The final chapter is dedicated to key topics such as spurious relationships, autocorrelation in regression, and multiple time series. Throughout the book, real-world examples illustrate step-by-step procedures and instructions using statistical software packages such as SAS, JMP, Minitab, SCA, and R. A related Web site features PowerPoint slides to accompany each chapter as well as the book's data sets. With its extensive use of graphics and examples to explain key concepts, Time Series Analysis and Forecasting by Example is an excellent book for courses on time series analysis at the upper-undergraduate and graduate levels. it also serves as a valuable resource for practitioners and researchers who carry out data and time series analysis in the fields of engineering, business, and economics.
Download or read book Applied Time Series written by T. M. J. A. Cooray and published by . This book was released on 2008 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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."--Jacket
