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Author: Dennis Tay Publisher: Routledge ISBN: 0429000170 Category : Language Arts & Disciplines Languages : en Pages : 176
Book Description
This volume serves as a comprehensive introduction to Time Series Analysis (TSA), used commonly in financial and engineering sciences, to demonstrate its potential to complement qualitative approaches in discourse analysis research. The book begins by discussing how time has previously been conceptualized in the literature, drawing on studies from variationist sociolinguistics, corpus linguistics, and Critical Discourse Analysis. The volume then segues into a discussion of how TSA is applied in other contexts in which observed values are expected to be dependent on earlier values, such as stock markets and sales figures, and introduces a range of discourse-specific contexts to show how the technique might be extended to analyze trends or shed further light on relevant themes in discourse over time. Each successive chapter features a different discourse context as a case study, from psychotherapy sessions, university lectures, and news articles, and looks at how studying different variables over time in each context – metaphors, involvement markers, and keywords, respectively – can contribute to a greater understanding of both present and future discourse activity in these settings. Taken together, this book highlights the value of TSA as a complementary approach to meaning-based analysis in discourse, making this ideal reading for graduate students and scholars in discourse analysis looking to employ quantitative methods in their research practice.
Author: Dennis Tay Publisher: Routledge ISBN: 0429000170 Category : Language Arts & Disciplines Languages : en Pages : 176
Book Description
This volume serves as a comprehensive introduction to Time Series Analysis (TSA), used commonly in financial and engineering sciences, to demonstrate its potential to complement qualitative approaches in discourse analysis research. The book begins by discussing how time has previously been conceptualized in the literature, drawing on studies from variationist sociolinguistics, corpus linguistics, and Critical Discourse Analysis. The volume then segues into a discussion of how TSA is applied in other contexts in which observed values are expected to be dependent on earlier values, such as stock markets and sales figures, and introduces a range of discourse-specific contexts to show how the technique might be extended to analyze trends or shed further light on relevant themes in discourse over time. Each successive chapter features a different discourse context as a case study, from psychotherapy sessions, university lectures, and news articles, and looks at how studying different variables over time in each context – metaphors, involvement markers, and keywords, respectively – can contribute to a greater understanding of both present and future discourse activity in these settings. Taken together, this book highlights the value of TSA as a complementary approach to meaning-based analysis in discourse, making this ideal reading for graduate students and scholars in discourse analysis looking to employ quantitative methods in their research practice.
Author: Zhongjie Xie Publisher: World Scientific ISBN: 9814583650 Category : Mathematics Languages : en Pages : 296
Book Description
This book is a monograph on case studies using time series analysis, which includes the main research works applied to practical projects by the author in the past 15 years. The works cover different problems in broad fields, such as: engineering, labour protection, astronomy, physiology, endocrinology, oil development, etc. The first part of this book introduces some basic knowledge of time series analysis which is necessary for the reader to understand the methods and the theory used in the procedure for solving problems. The second part is the main part of this book — case studies in different fields.
Author: Youseop Shin Publisher: Univ of California Press ISBN: 0520293169 Category : Law Languages : en Pages : 244
Book Description
"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.
Author: Deepesh Machiwal Publisher: Springer Science & Business Media ISBN: 9400718616 Category : Science Languages : en Pages : 316
Book Description
There is a dearth of relevant books dealing with both theory and application of time series analysis techniques, particularly in the field of water resources engineering. Therefore, many hydrologists and hydrogeologists face difficulties in adopting time series analysis as one of the tools for their research. This book fills this gap by providing a proper blend of theoretical and practical aspects of time sereies analysis. It deals with a comprehensive overview of time series characteristics in hydrology/water resources engineering, various tools and techniques for analyzing time series data, theoretical details of 31 available statistical tests along with detailed procedures for applying them to real-world time series data, theory and methodology of stochastic modelling, and current status of time series analysis in hydrological sciences. In adition, it demonstrates the application of most time series tests through a case study as well as presents a comparative performance evaluation of various time series tests, together with four invited case studies from India and abroad. This book will not only serve as a textbook for the students and teachers in water resources engineering but will also serve as the most comprehensive reference to educate researchers/scientists about the theory and practice of time series analysis in hydrological sciences. This book will be very useful to the students, researchers, teachers and professionals involved in water resources, hydrology, ecology, climate change, earth science, and environmental studies.
Author: Rob J Hyndman Publisher: OTexts ISBN: 0987507117 Category : Business & Economics Languages : en Pages : 380
Book Description
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.
Author: Folgert Karsdorp Publisher: Princeton University Press ISBN: 0691172366 Category : Computers Languages : en Pages : 352
Book Description
A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations
Author: Mark A. Kramer Publisher: MIT Press ISBN: 0262529378 Category : Science Languages : en Pages : 385
Book Description
A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.
Author: Yanchang Zhao Publisher: Academic Press ISBN: 012397271X Category : Mathematics Languages : en Pages : 251
Book Description
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work
Author: Gábor Békés Publisher: Cambridge University Press ISBN: 1108483011 Category : Business & Economics Languages : en Pages : 741
Book Description
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Author: J.O. Ramsay Publisher: Springer ISBN: 0387224653 Category : Mathematics Languages : en Pages : 194
Book Description
This book contains the ideas of functional data analysis by a number of case studies. The case studies are accessible to research workers in a wide range of disciplines. Every reader should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of thought. There is an associated web site with MATLABr and S?PLUSr implementations of the methods discussed.
Author: Dennis Tay
Author: Dennis Tay
Author: Zhongjie Xie
Author: Youseop Shin
Author: Deepesh Machiwal
Author: Rob J Hyndman
Author: Folgert Karsdorp
Author: Mark A. Kramer
Author: Yanchang Zhao
Author: Gábor Békés
Author: J.O. Ramsay