Time Series Analysis Papers

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Time Series Analysis in the Social Sciences

Author : Youseop Shin
Publisher : Univ of California Press
ISBN 13 : 0520293169
Total Pages : 244 pages
Book Rating : 4.5/5 (22 download)

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Book Synopsis Time Series Analysis in the Social Sciences by : Youseop Shin

Download or read book Time Series Analysis in the Social Sciences written by Youseop Shin and published by Univ of California Press. This book was released on 2017-02-07 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on fundamental elements of time-series analysis that social scientists need to understand to employ time-series analysis for their research and practice. Avoiding extraordinary mathematical materials, this book explains univariate time-series analysis step-by-step, from the preliminary visual analysis through the modeling of seasonality, trends, and residuals to the prediction and the evaluation of estimated models. Then, this book explains smoothing, multiple time-series analysis, and interrupted time-series analysis. At the end of each step, this book coherently provides an analysis of the monthly violent-crime rates as an example."--Provided by publisher.

Forecasting: principles and practice

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis Forecasting: principles and practice by : Rob J Hyndman

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Time Series Analysis and Its Applications

Author : Robert H. Shumway
Publisher :
ISBN 13 : 9781475732627
Total Pages : 568 pages
Book Rating : 4.7/5 (326 download)

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Book Synopsis Time Series Analysis and Its Applications by : Robert H. Shumway

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:

Multivariate Time Series Analysis in Climate and Environmental Research

Author : Zhihua Zhang
Publisher : Springer
ISBN 13 : 3319673408
Total Pages : 293 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Multivariate Time Series Analysis in Climate and Environmental Research by : Zhihua Zhang

Download or read book Multivariate Time Series Analysis in Climate and Environmental Research written by Zhihua Zhang and published by Springer. This book was released on 2017-11-09 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.

Time Series Analysis Univariate and Multivariate Methods

Author : William W. S. Wei
Publisher : Pearson
ISBN 13 : 9780134995366
Total Pages : 648 pages
Book Rating : 4.9/5 (953 download)

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Book Synopsis Time Series Analysis Univariate and Multivariate Methods by : William W. S. Wei

Download or read book Time Series Analysis Univariate and Multivariate Methods written by William W. S. Wei and published by Pearson. This book was released on 2018-03-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its broad coverage of methodology, this comprehensive book is a useful learning and reference tool for those in applied sciences where analysis and research of time series is useful. Its plentiful examples show the operational details and purpose of a variety of univariate and multivariate time series methods. Numerous figures, tables and real-life time series data sets illustrate the models and methods useful for analyzing, modeling, and forecasting data collected sequentially in time. The text also offers a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.

Practical Time Series Analysis

Author : Aileen Nielsen
Publisher : O'Reilly Media
ISBN 13 : 1492041629
Total Pages : 500 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical Time Series Analysis by : Aileen Nielsen

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

Nonlinear Time Series Analysis

Author : Holger Kantz
Publisher : Cambridge University Press
ISBN 13 : 9780521529020
Total Pages : 390 pages
Book Rating : 4.5/5 (29 download)

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Book Synopsis Nonlinear Time Series Analysis by : Holger Kantz

Download or read book Nonlinear Time Series Analysis written by Holger Kantz and published by Cambridge University Press. This book was released on 2004 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paradigm of deterministic chaos has influenced thinking in many fields of science. Chaotic systems show rich and surprising mathematical structures. In the applied sciences, deterministic chaos provides a striking explanation for irregular behaviour and anomalies in systems which do not seem to be inherently stochastic. The most direct link between chaos theory and the real world is the analysis of time series from real systems in terms of nonlinear dynamics. Experimental technique and data analysis have seen such dramatic progress that, by now, most fundamental properties of nonlinear dynamical systems have been observed in the laboratory. Great efforts are being made to exploit ideas from chaos theory wherever the data displays more structure than can be captured by traditional methods. Problems of this kind are typical in biology and physiology but also in geophysics, economics, and many other sciences.

The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis

Author : Todd D. Little
Publisher : Oxford University Press
ISBN 13 : 0199934908
Total Pages : 784 pages
Book Rating : 4.1/5 (999 download)

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Book Synopsis The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis by : Todd D. Little

Download or read book The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis written by Todd D. Little and published by Oxford University Press. This book was released on 2013-02-01 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.

Least Squares Support Vector Machines

Author : Johan A. K. Suykens
Publisher : World Scientific
ISBN 13 : 9789812381514
Total Pages : 318 pages
Book Rating : 4.3/5 (815 download)

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Book Synopsis Least Squares Support Vector Machines by : Johan A. K. Suykens

Download or read book Least Squares Support Vector Machines written by Johan A. K. Suykens and published by World Scientific. This book was released on 2002 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is discussed, together with methods for imposing spareness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LS-SVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LS-SVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.

Time Series Analysis

Author : Jonathan D. Cryer
Publisher : Springer Science & Business Media
ISBN 13 : 0387759581
Total Pages : 501 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Time Series Analysis by : Jonathan D. Cryer

Download or read book Time Series Analysis written by Jonathan D. Cryer and published by Springer Science & Business Media. This book was released on 2008-04-04 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Research Papers in Statistical Inference for Time Series and Related Models

Author : Yan Liu
Publisher : Springer Nature
ISBN 13 : 9819908035
Total Pages : 591 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Research Papers in Statistical Inference for Time Series and Related Models by : Yan Liu

Download or read book Research Papers in Statistical Inference for Time Series and Related Models written by Yan Liu and published by Springer Nature. This book was released on 2023-05-31 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.

Principles of Forecasting

Author : J.S. Armstrong
Publisher : Springer Science & Business Media
ISBN 13 : 9780792374015
Total Pages : 880 pages
Book Rating : 4.3/5 (74 download)

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Book Synopsis Principles of Forecasting by : J.S. Armstrong

Download or read book Principles of Forecasting written by J.S. Armstrong and published by Springer Science & Business Media. This book was released on 2001 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.

Introduction to Time Series and Forecasting

Author : Peter J. Brockwell
Publisher : Springer Science & Business Media
ISBN 13 : 1475725264
Total Pages : 429 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell

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.

Practical Time Series Analysis

Author : Dr. Avishek Pal
Publisher : Packt Publishing Ltd
ISBN 13 : 178829419X
Total Pages : 238 pages
Book Rating : 4.7/5 (882 download)

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Book Synopsis Practical Time Series Analysis by : Dr. Avishek Pal

Download or read book Practical Time Series Analysis written by Dr. Avishek Pal and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step by Step guide filled with real world practical examples. About This Book Get your first experience with data analysis with one of the most powerful types of analysis—time-series. Find patterns in your data and predict the future pattern based on historical data. Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project Develop an understanding of loading, exploring, and visualizing time-series data Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series Take advantage of exponential smoothing to tackle noise in time series data Learn how to use auto-regressive models to make predictions using time-series data Build predictive models on time series using techniques based on auto-regressive moving averages Discover recent advancements in deep learning to build accurate forecasting models for time series Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.

The Analysis of Time Series

Author : Chris Chatfield
Publisher : CRC Press
ISBN 13 : 1498795641
Total Pages : 415 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis The Analysis of Time Series by : Chris Chatfield

Download or read book The Analysis of Time Series written by Chris Chatfield and published by CRC Press. This book was released on 2019-04-25 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear systems, state-space models, the Kalman filters, nonlinear models, volatility models, and multivariate models.

Introduction to Time Series Analysis and Forecasting

Author : Douglas C. Montgomery
Publisher : John Wiley & Sons
ISBN 13 : 1118745159
Total Pages : 670 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Introduction to Time Series Analysis and Forecasting by : Douglas C. Montgomery

Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.

A Course in Time Series Analysis

Author : Daniel Peña
Publisher : John Wiley & Sons
ISBN 13 : 1118031229
Total Pages : 494 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis A Course in Time Series Analysis by : Daniel Peña

Download or read book A Course in Time Series Analysis written by Daniel Peña and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.