Multivariate Time Series Analysis And Applications

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Multivariate Time Series Analysis And Applications

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Author : William W. S. Wei
language : en
Publisher: John Wiley & Sons
Release Date : 2018-12-31

Multivariate Time Series Analysis And Applications written by William W. S. Wei 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 2018-12-31 with Mathematics categories.

An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.

Multivariate Time Series Analysis

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Author : Ruey S. Tsay
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-11

Multivariate Time Series Analysis written by Ruey S. Tsay 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 2013-11-11 with Mathematics categories.

An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.

Theory And Applications Of Time Series Analysis

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Author : Olga Valenzuela
language : en
Publisher: Springer Nature
Release Date : 2023-11-09

Theory And Applications Of Time Series Analysis written by Olga Valenzuela and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-09 with Mathematics categories.

This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address modern theoretical aspects of time series analysis, forecasting and prediction, with applications to various disciplines, including econometrics and energy research. The broad range of topics discussed, including matters of particular relevance for sustainable development, will give readers a modern perspective on the subject. The included contributions were originally presented at the 8th International Conference on Time Series and Forecasting, ITISE 2022, held in Gran Canaria, Spain, June 27-30, 2022. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.

Time Series Analysis

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Author : William W. S. Wei
language : en
Publisher: Addison-Wesley Longman
Release Date : 2006

Time Series Analysis written by William W. S. Wei and has been published by Addison-Wesley Longman this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.

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. Overview. Fundamental Concepts. Stationary Time Series Models. Nonstationary Time Series Models. Forecasting. Model Identification. Parameter Estimation, Diagnostic Checking, and Model Selection. Seasonal Time Series Models. Testing for a Unit Root. Intervention Analysis and Outlier Detection. Fourier Analysis. Spectral Theory of Stationary Processes. Estimation of the Spectrum. Transfer Function Models. Time Series Regression and GARCH Models. Vector Time Series Models. More on Vector Time Series. State Space Models and the Kalman Filter. Long Memory and Nonlinear Processes. Aggregation and Systematic Sampling in Time Series. For all readers interested in time series analysis.

Multi And Megavariate Data Analysis Basic Principles And Applications

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Author : L. Eriksson
language : en
Publisher: Umetrics Academy
Release Date : 2013-07-01

Multi And Megavariate Data Analysis Basic Principles And Applications written by L. Eriksson and has been published by Umetrics Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-01 with Mathematics categories.

To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.

Introduction To Time Series Analysis

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Author : Vikas Rathi
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Introduction To Time Series Analysis written by Vikas Rathi and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.

"Introduction to Time Series Analysis" is a comprehensive guide exploring the world of time series data, blending theoretical insights with practical applications. Time series analysis is crucial across disciplines like economics, finance, engineering, and environmental science, helping us understand past patterns, forecast future trends, and make informed decisions. We cater to students, researchers, and practitioners seeking a deep understanding of time series analysis. Covering a range of topics from foundational concepts to advanced techniques, we ensure readers gain a holistic view of the subject. With clear explanations, illustrative examples, and real-world case studies, this book equips readers with the knowledge and skills needed to tackle complex time series data effectively. The book provides a solid theoretical foundation in time series analysis, covering topics such as time series decomposition, forecasting methods, and advanced modeling techniques. Emphasis is placed on practical applications, with real-world examples and case studies illustrating concepts and methodologies. The text is written in clear and accessible language, suitable for readers with varying expertise, and acknowledges the interdisciplinary nature of time series analysis, exploring its applications across different fields. Whether you're a student, researcher, or practitioner, "Introduction to Time Series Analysis" offers valuable insights and practical guidance to harness the power of time series data for informed decision-making.

Handbook Of Regression Analysis With Applications In R

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Author : Samprit Chatterjee
language : en
Publisher: John Wiley & Sons
Release Date : 2020-07-30

Handbook Of Regression Analysis With Applications In R written by Samprit Chatterjee 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 2020-07-30 with Mathematics categories.

Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methods Smoothing methods Tree-based methods In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.

Alternative Methods For Multivariate Time Series Analysis With Applications To U S Money Output Data

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Author : Stefan Mittnik
language : en
Publisher:
Release Date : 1987

Alternative Methods For Multivariate Time Series Analysis With Applications To U S Money Output Data written by Stefan Mittnik and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with categories.

Database Systems For Advanced Applications

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Author : Makoto Onizuka
language : en
Publisher: Springer Nature
Release Date : 2024-09-30

Database Systems For Advanced Applications written by Makoto Onizuka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Mathematics categories.

The seven-volume set LNCS 14850-14856 constitutes the proceedings of the 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, held in Gifu, Japan, in July 2024. The total of 147 full papers, along with 85 short papers, presented together in this seven-volume set was carefully reviewed and selected from 722 submissions. Additionally, 14 industrial papers, 18 demo papers and 6 tutorials are included. The conference presents papers on subjects such as: Part I: Spatial and temporal data; database core technology; federated learning. Part II: Machine learning; text processing. Part III: Recommendation; multi-media. Part IV: Privacy and security; knowledge base and graphs. Part V: Natural language processing; large language model; time series and stream data. Part VI: Graph and network; hardware acceleration. Part VII: Emerging application; industry papers; demo papers.

Database Systems For Advanced Applications

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Author : Xin Wang
language : en
Publisher: Springer Nature
Release Date : 2023-04-13

Database Systems For Advanced Applications written by Xin Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-13 with Mathematics categories.

The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China. The total of 125 full papers, along with 66 short papers, are presented together in this four-volume set was carefully reviewed and selected from 652 submissions. Additionally, 15 industrial papers, 15 demo papers and 4 PhD consortium papers are included. The conference presents papers on subjects such as model, graph, learning, performance, knowledge, time, recommendation, representation, attention, prediction, and network.