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Author : Jörg Breitung
Publisher :
ISBN 13 : 9783865580979
Total Pages : 29 pages
Book Rating : 4.5/5 (89 download)
Download or read book Dynamic Factor Models written by Jörg Breitung and published by . This book was released on 2005 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michael P. Clements
Publisher : OUP USA
ISBN 13 : 0195398645
Total Pages : 732 pages
Book Rating : 4.1/5 (953 download)
Download or read book The Oxford Handbook of Economic Forecasting written by Michael P. Clements and published by OUP USA. This book was released on 2011-07-08 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.
Author : Olaf Hübler
Publisher : Springer Science & Business Media
ISBN 13 : 3540326936
Total Pages : 236 pages
Book Rating : 4.5/5 (43 download)
Download or read book Modern Econometric Analysis written by Olaf Hübler and published by Springer Science & Business Media. This book was released on 2007-04-29 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book leading German econometricians in different fields present survey articles of the most important new methods in econometrics. The book gives an overview of the field and it shows progress made in recent years and remaining problems.
Author : Matteo Barigozzi
Publisher : Springer Nature
ISBN 13 : 303161853X
Total Pages : 617 pages
Book Rating : 4.0/5 (316 download)
Download or read book Recent Advances in Econometrics and Statistics written by Matteo Barigozzi and published by Springer Nature. This book was released on with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Giovanni Petris
Publisher : Springer Science & Business Media
ISBN 13 : 0387772383
Total Pages : 258 pages
Book Rating : 4.3/5 (877 download)
Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Author : Ana Jesus Lopez-Menendez
Publisher : MDPI
ISBN 13 : 3039364871
Total Pages : 200 pages
Book Rating : 4.0/5 (393 download)
Download or read book Entropy Application for Forecasting written by Ana Jesus Lopez-Menendez and published by MDPI. This book was released on 2020-12-29 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field.
Author : Jushan Bai
Publisher : Now Publishers Inc
ISBN 13 : 1601981449
Total Pages : 90 pages
Book Rating : 4.6/5 (19 download)
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Author : Nguyen Ngoc Thach
Publisher : Springer Nature
ISBN 13 : 3031591100
Total Pages : 724 pages
Book Rating : 4.0/5 (315 download)
Download or read book Partial Identification in Econometrics and Related Topics written by Nguyen Ngoc Thach and published by Springer Nature. This book was released on with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Journal of Econometrics, Volume 122, Issue 1 written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frédéric Ferraty
Publisher : Springer Science & Business Media
ISBN 13 : 3790827363
Total Pages : 322 pages
Book Rating : 4.7/5 (98 download)
Download or read book Recent Advances in Functional Data Analysis and Related Topics written by Frédéric Ferraty and published by Springer Science & Business Media. This book was released on 2011-06-15 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: New technologies allow us to handle increasingly large datasets, while monitoring devices are becoming ever more sophisticated. This high-tech progress produces statistical units sampled over finer and finer grids. As the measurement points become closer, the data can be considered as observations varying over a continuum. This intrinsic continuous data (called functional data) can be found in various fields of science, including biomechanics, chemometrics, econometrics, environmetrics, geophysics, medicine, etc. The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA). Today, FDA is certainly one of the most motivating and popular statistical topics due to its impact on crucial societal issues (health, environment, etc). This is why the FDA statistical community is rapidly growing, as are the statistical developments . Therefore, it is necessary to organize regular meetings in order to provide a state-of-art review of the recent advances in this fascinating area. This book collects selected and extended papers presented at the second International Workshop of Functional and Operatorial Statistics (Santander, Spain, 16-18 June, 2011), in which many outstanding experts on FDA will present the most relevant advances in this pioneering statistical area. Undoubtedly, these proceedings will be an essential resource for academic researchers, master students, engineers, and practitioners not only in statistics but also in numerous related fields of application.
Author : William W. S. Wei
Publisher : John Wiley & Sons
ISBN 13 : 1119502853
Total Pages : 536 pages
Book Rating : 4.1/5 (195 download)
Download or read book Multivariate Time Series Analysis and Applications written by William W. S. Wei and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Ruey S. Tsay
Publisher : John Wiley & Sons
ISBN 13 : 1118617754
Total Pages : 414 pages
Book Rating : 4.1/5 (186 download)
Download or read book Multivariate Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2013-11-11 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Jianqing Fan
Publisher : Cambridge University Press
ISBN 13 : 1107191173
Total Pages : 394 pages
Book Rating : 4.1/5 (71 download)
Download or read book The Elements of Financial Econometrics written by Jianqing Fan and published by Cambridge University Press. This book was released on 2017-03-23 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: A compact, master's-level textbook on financial econometrics, focusing on methodology and including real financial data illustrations throughout. The mathematical level is purposely kept moderate, allowing the power of the quantitative methods to be understood without too much technical detail.
Author : William D. Penny
Publisher : Elsevier
ISBN 13 : 0080466508
Total Pages : 689 pages
Book Rating : 4.0/5 (84 download)
Download or read book Statistical Parametric Mapping: The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)
Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Author : Aman Ullah
Publisher : CRC Press
ISBN 13 : 9781420070361
Total Pages : 532 pages
Book Rating : 4.0/5 (73 download)
Download or read book Handbook of Empirical Economics and Finance written by Aman Ullah and published by CRC Press. This book was released on 2016-04-19 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Empirical Economics and Finance explores the latest developments in the analysis and modeling of economic and financial data. Well-recognized econometric experts discuss the rapidly growing research in economics and finance and offer insight on the future direction of these fields. Focusing on micro models, the first group of chapters describes the statistical issues involved in the analysis of econometric models with cross-sectional data often arising in microeconomics. The book then illustrates time series models that are extensively used in empirical macroeconomics and finance. The last set of chapters explores the types of panel data and spatial models that are becoming increasingly significant in analyzing complex economic behavior and policy evaluations. This handbook brings together both background material and new methodological and applied results that are extremely important to the current and future frontiers in empirical economics and finance. It emphasizes inferential issues that transpire in the analysis of cross-sectional, time series, and panel data-based empirical models in economics, finance, and related disciplines.
Author : David J. C. MacKay
Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)
Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
