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Author: Jelke G. Bethlehem
Publisher: Springer Science & Business Media
ISBN: 9783790813265
Category : Business & Economics
Languages : en
Pages : 556
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Book Description
This book contains the keynote, invited and full contributed papers presented at COMPSTAT 2000, held in Utrecht. The papers range over all aspects of the link between statistical theory and applied statistics, with special attention for developments in the area of official statistics. The papers have been thoroughly refereed.
Author: Jelke G. Bethlehem
Publisher: Springer Science & Business Media
ISBN: 9783790813265
Category : Business & Economics
Languages : en
Pages : 556
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Book Description
This book contains the keynote, invited and full contributed papers presented at COMPSTAT 2000, held in Utrecht. The papers range over all aspects of the link between statistical theory and applied statistics, with special attention for developments in the area of official statistics. The papers have been thoroughly refereed.
Author: Víctor Gómez
Publisher:
ISBN: 9788477935131
Category : Box-Jenkins forecasting
Languages : en
Pages : 124
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Book Description
Author: Haim Y. Bleikh
Publisher: CRC Press
ISBN: 1317010175
Category : Business & Economics
Languages : en
Pages : 148
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Book Description
In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.
Author: Daniel Peña
Publisher: John Wiley & Sons
ISBN: 1118031229
Category : Mathematics
Languages : en
Pages : 494
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Book Description
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.
Author: Estela Bee Dagum
Publisher: Springer
ISBN: 3319318225
Category : Business & Economics
Languages : en
Pages : 293
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Book Description
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Author: Francesco Palumbo
Publisher: Springer Science & Business Media
ISBN: 3642037399
Category : Mathematics
Languages : en
Pages : 473
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Book Description
The volume provides results from the latest methodological developments in data analysis and classification and highlights new emerging subjects within the field. It contains articles about statistical models, classification, cluster analysis, multidimensional scaling, multivariate analysis, latent variables, knowledge extraction from temporal data, financial and economic applications, and missing values. Papers cover both theoretical and empirical aspects.
Author: Fernandes, Gonçalo Poeta
Publisher: IGI Global
ISBN: 1668469871
Category : Business & Economics
Languages : en
Pages : 410
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Book Description
Tourism and hospitality are increasingly becoming more complex, having grown exponentially over the last decade. As the industry becomes more complex, new demands arise regarding its overall organization and operations, which call for not only more experienced and specialized staff, but also advanced technological solutions that support new paradigms and expectations. The Handbook of Research on Innovation, Differentiation, and New Technologies in Tourism, Hotels, and Food Service discusses the current changes and challenges in tourism and hospitality. Covering key topics such as entrepreneurship, local development, and technology, this major reference work is ideal for managers, entrepreneurs, business owners, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Author: Víctor Gómez
Publisher: Springer Nature
ISBN: 3030207900
Category : Computers
Languages : en
Pages : 355
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Book Description
This book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details.
Author: Víctor Gómez
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 48
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Book Description
Author: Raghu Nandan Sengupta
Publisher: CRC Press
ISBN: 1482282569
Category : Business & Economics
Languages : en
Pages : 1042
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Book Description
This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
