Spectral Analysis of Time-series Data

Author: Rebecca M. Warner

Publisher: Guilford Press

ISBN: 9781572303386

Category: Social Science

Page: 225

View: 6434

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This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.

Time Series Analysis for the Social Sciences

Author: Janet M. Box-Steffensmeier,John R. Freeman,Matthew P. Hitt,Jon C. W. Pevehouse

Publisher: Cambridge University Press

ISBN: 1316060500

Category: Political Science

Page: N.A

View: 2988

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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.

Time Series Analysis and Its Applications

With R Examples

Author: Robert H. Shumway,David S. Stoffer

Publisher: Springer

ISBN: 3319524526

Category: Mathematics

Page: 562

View: 4203

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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.

Time Series Analysis in the Social Sciences

The Fundamentals

Author: Youseop Shin

Publisher: Univ of California Press

ISBN: 0520293169

Category: Mathematics

Page: 272

View: 2953

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"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.

The Spectral Analysis of Time Series

Author: Lambert H. Koopmans

Publisher: Elsevier

ISBN: 9780080541563

Category: Mathematics

Page: 366

View: 5689

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To tailor time series models to a particular physical problem and to follow the working of various techniques for processing and analyzing data, one must understand the basic theory of spectral (frequency domain) analysis of time series. This classic book provides an introduction to the techniques and theories of spectral analysis of time series. In a discursive style, and with minimal dependence on mathematics, the book presents the geometric structure of spectral analysis. This approach makes possible useful, intuitive interpretations of important time series parameters and provides a unified framework for an otherwise scattered collection of seemingly isolated results. The books strength lies in its applicability to the needs of readers from many disciplines with varying backgrounds in mathematics. It provides a solid foundation in spectral analysis for fields that include statistics, signal process engineering, economics, geophysics, physics, and geology. Appendices provide details and proofs for those who are advanced in math. Theories are followed by examples and applications over a wide range of topics such as meteorology, seismology, and telecommunications. Topics covered include Hilbert spaces; univariate models for spectral analysis; multivariate spectral models; sampling, aliasing, and discrete-time models; real-time filtering; digital filters; linear filters; distribution theory; sampling properties ofspectral estimates; and linear prediction. Hilbert spaces univariate models for spectral analysis multivariate spectral models sampling, aliasing, and discrete-time models real-time filtering digital filters linear filters distribution theory sampling properties of spectral estimates linear prediction

Data Analysis Methods in Physical Oceanography

Author: Richard E. Thomson,William J. Emery

Publisher: Newnes

ISBN: 0123877830

Category: Science

Page: 728

View: 2518

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Data Analysis Methods in Physical Oceanography, Third Edition is a practical reference to established and modern data analysis techniques in earth and ocean sciences. Its five major sections address data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. The revised Third Edition updates the instrumentation used to collect and analyze physical oceanic data and adds new techniques including Kalman Filtering. Additionally, the sections covering spectral, wavelet, and harmonic analysis techniques are completely revised since these techniques have attracted significant attention over the past decade as more accurate and efficient data gathering and analysis methods. Completely updated and revised to reflect new filtering techniques and major updating of the instrumentation used to collect and analyze data Co-authored by scientists from academe and industry, both of whom have more than 30 years of experience in oceanographic research and field work Significant revision of sections covering spectral, wavelet, and harmonic analysis techniques Examples address typical data analysis problems yet provide the reader with formulaic “recipes for working with their own data Significant expansion to 350 figures, illustrations, diagrams and photos

The SAGE Encyclopedia of Social Science Research Methods

Author: Michael Lewis-Beck,Alan E Bryman,Tim Futing Liao

Publisher: SAGE

ISBN: 9780761923633

Category: Social Science

Page: 1305

View: 9970

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"The first encyclopedia to cover inclusively both quantitative and qualitative research approaches, this set provides clear explanations of 1,000 methodologies, avoiding mathematical equations when possible with liberal cross-referencing and bibliographies. Each volume includes a list of works cited, and the third contains a comprehensive index and lists of person names, organizations, books, tests, software, major concepts, surveys, and methodologies."--"Reference that rocks," American Libraries, May 2005.

Approaches and Methodologies in the Social Sciences

A Pluralist Perspective

Author: Donatella Della Porta,Michael Keating

Publisher: Cambridge University Press

ISBN: 1139474596

Category: Political Science

Page: N.A

View: 695

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A revolutionary textbook introducing masters and doctoral students to the major research approaches and methodologies in the social sciences. Written by an outstanding set of scholars, and derived from successful course teaching, this volume will empower students to choose their own approach to research, to justify this approach, and to situate it within the discipline. It addresses questions of ontology, epistemology and philosophy of social science, and proceeds to issues of methodology and research design essential for producing a good research proposal. It also introduces researchers to the main issues of debate and contention in the methodology of social sciences, identifying commonalities, historic continuities and genuine differences.

Introduction to Time Series and Forecasting

Author: Peter J. Brockwell,Richard A. Davis

Publisher: Springer

ISBN: 3319298542

Category: Mathematics

Page: 425

View: 5421

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This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. 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. Many additional special topics are also covered. New to this edition: A chapter devoted to Financial Time Series Introductions to Brownian motion, Lévy processes and Itô calculus An expanded section on continuous-time ARMA processes

Time-Series Analysis

A Comprehensive Introduction for Social Scientists

Author: John M. Gottman

Publisher: Cambridge University Press

ISBN: 0521235979

Category: Mathematics

Page: 400

View: 2868

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This book is a comprehensive introduction to all the major time-series techniques, both time-domain and frequency-domain. It includes work on linear models that simplify the solution of univariate and multivariate problems. The author begins with a non-mathematical overview and provides throughout, easy-to-understand, fully worked examples drawn from real studies in psychology and sociology.

Time Series Analysis for the Social Sciences

Author: Janet M. Box-Steffensmeier,John R. Freeman,Jon C. W. Pevehouse,Matthew P. Hitt

Publisher: Cambridge University Press

ISBN: 0521871166

Category: Political Science

Page: 272

View: 9594

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This book provides instruction and examples of the core methods in time series econometrics, drawing from several main fields of the social sciences.

Time Series Analysis

Univariate and Multivariate Methods

Author: William W. S. Wei,William W. S.. Wei,David P. Reilly

Publisher: Addison-Wesley

ISBN: N.A

Category: Mathematics

Page: 478

View: 7887

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Emphasizing and providing a broad coverage of methodology, this comprehensive book is of interest to a variety of people in the applied sciences who want to know how time series can be used in their areas of research. The book provides useful examples that show the operational details and purpose of the methods. It covers methods extensively, and illustrates them with numerous figures, tables and examples using many real-life time series data sets. The book also introduces univariate and multivariate time series models and methods which are useful for analyzing, modeling, and forecasting data collected sequentially in time, and provides a balanced treatment between theory and applications. Time Series Analysis is a thorough introduction to both time-domain and frequency-domain analyses, and it gives extensive coverage of both univariate and multivariate time series methods, including the most recently developed techniques in the field.

Time Series Analysis in Meteorology and Climatology

An Introduction

Author: Claude Duchon,Robert Hale

Publisher: John Wiley & Sons

ISBN: 1119960983

Category: Science

Page: 256

View: 5580

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Time Series Analysis in Meteorology and Climatology provides an accessible overview of this notoriously difficult subject. Clearly structured throughout, the authors develop sufficient theoretical foundation to understand the basis for applying various analytical methods to a time series and show clearly how to interpret the results. Taking a unique approach to the subject, the authors use a combination of theory and application to real data sets to enhance student understanding throughout the book. This book is written for those students that have a data set in the form of a time series and are confronted with the problem of how to analyse this data. Each chapter covers the various methods that can be used to carry out this analysis with coverage of the necessary theory and its application. In the theoretical section topics covered include; the mathematical origin of spectrum windows, leakage of variance and understanding spectrum windows. The applications section includes real data sets for students to analyse. Scalar variables are used for ease of understanding for example air temperatures, wind speed and precipitation. Students are encouraged to write their own computer programmes and data sets are provided to enable them to recognize quickly whether their programme is working correctly- one data set is provided with artificial data and the other with real data where the students are required to physically interpret the results of their periodgram analysis. Based on the acclaimed and long standing course at the University of Oklahoma and part of the RMetS Advancing Weather and Climate Science Series, this book is distinct in its approach to the subject matter in that it is written specifically for readers in meteorology and climatology and uses a mix of theory and application to real data sets.

Advances in Configural Frequency Analysis

Author: Alexander von Eye,Patrick Mair,Eun Young Mun

Publisher: Guilford Press

ISBN: 1606237195

Category: Psychology

Page: 306

View: 7405

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Using real-world data examples, this authoritative book shows how to use the latest configural frequency analysis (CFA) techniques to analyze categorical data. Some of the techniques are presented here for the first time. In contrast to such methods as log-linear modeling, which focus on relationships among variables, CFA allows researchers to evaluate differences and change at the level of individual cells in a table. Illustrated are ways to identify and test for cell configurations that are either consistent with or contrary to hypothesized patterns (the types and antitypes of CFA); control for potential covariates that might influence observed results; develop innovative prediction models; address questions of moderation and mediation; and analyze intensive longitudinal data. The book also describes free software applications for executing CFA. This book will be invaluable to researchers and graduate students in psychology, education, management, public health, sociology, and other social, behavioral, and health science disciplines. It will also serve as a supplemental text in graduate-level courses on categorical data analysis, longitudinal analysis, and person-oriented research.

Time Series

Modeling, Computation, and Inference

Author: Raquel Prado,Mike West

Publisher: CRC Press

ISBN: 1439882754

Category: Mathematics

Page: 368

View: 8648

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Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.

ITSM for Windows

A User’s Guide to Time Series Modelling and Forecasting

Author: Peter J. Brockwell,Richard A. Davis

Publisher: Springer

ISBN: 1461226767

Category: Computers

Page: 118

View: 3779

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The analysis of time series data is an important aspect of data analysis across a wide range of disciplines, including statistics, mathematics, business, engineering, and the natural and social sciences. This package provides both an introduction to time series analysis and an easy-to-use version of a well-known time series computing package called Interactive Time Series Modelling. The programs in the package are intended as a supplement to the text Time Series: Theory and Methods, 2nd edition, also by Peter J. Brockwell and Richard A. Davis. Many researchers and professionals will appreciate this straightforward approach enabling them to run desk-top analyses of their time series data. Amongst the many facilities available are tools for: ARIMA modelling, smoothing, spectral estimation, multivariate autoregressive modelling, transfer-function modelling, forecasting, and long-memory modelling. This version is designed to run under Microsoft Windows 3.1 or later. It comes with two diskettes: one suitable for less powerful machines (IBM PC 286 or later with 540K available RAM and 1.1 MB of hard disk space) and one for more powerful machines (IBM PC 386 or later with 8MB of RAM and 2.6 MB of hard disk space available).

Graphics Recognition. Ten Years Review and Future Perspectives

6th International Workshop, GREC 2005, Hong Kong, China, August 25-26, 2005, Revised Selected Papers

Author: Wenyin Liu,Josep Lladós

Publisher: Springer Science & Business Media

ISBN: 3540347119

Category: Computers

Page: 428

View: 3355

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This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Graphics Recognition, GREC 2005, held in Hong Kong, China in August 2005.The 37 revised full papers presented together with a panel discussion report were carefully selected and improved during two rounds of reviewing and revision. The papers are organized in topical sections on engineering drawings vectorization and recognition, symbol recognition, graphic image analysis, structural document analysis, sketching and online graphics recognition, curves and shape processing, and graphics recognition contest results.nbsp;