Time Series Analysis and Forecasting, Ignacio Rojas; H?ctor Pomares; Olga Valenzuela
Автор: Hamilton, James Название: Time Series Analysis ISBN: 0691042896 ISBN-13(EAN): 9780691042893 Издательство: Wiley Рейтинг: Цена: 11088.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A graduate-level text which describes the recent dramatic changes that have taken place in the way that researchers analyze economic and financial time series. It explores such important innovations as vector regression, nonlinear time series models and the generalized methods of moments.
Автор: Lutkepohl, Helmut Название: New Introduction to Multiple Time Series Analysis ISBN: 3540262393 ISBN-13(EAN): 9783540262398 Издательство: Springer Рейтинг: Цена: 16513.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It provides a detailed introduction to the main steps of analyzing multiple time series, model specification, estimation, model checking, and for using the models for economic analysis and forecasting.
Introduces the latest developments in forecasting in advanced quantitative data analysis
This book presents advanced univariate multiple regressions, which can directly be used to forecast their dependent variables, evaluate their in-sample forecast values, and compute forecast values beyond the sample period. Various alternative multiple regressions models are presented based on a single time series, bivariate, and triple time-series, which are developed by taking into account specific growth patterns of each dependent variables, starting with the simplest model up to the most advanced model. Graphs of the observed scores and the forecast evaluation of each of the models are offered to show the worst and the best forecast models among each set of the models of a specific independent variable.
Advanced Time Series Data Analysis: Forecasting Using EViews provides readers with a number of modern, advanced forecast models not featured in any other book. They include various interaction models, models with alternative trends (including the models with heterogeneous trends), and complete heterogeneous models for monthly time series, quarterly time series, and annually time series. Each of the models can be applied by all quantitative researchers.
Presents models that are all classroom tested
Contains real-life data samples
Contains over 350 equation specifications of various time series models
Contains over 200 illustrative examples with special notes and comments
Applicable for time series data of all quantitative studies
Advanced Time Series Data Analysis: Forecasting Using EViews will appeal to researchers and practitioners in forecasting models, as well as those studying quantitative data analysis. It is suitable for those wishing to obtain a better knowledge and understanding on forecasting, specifically the uncertainty of forecast values.
Описание: This is a revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970. It focuses on practical techniques throughout, rather than a rigorous mathematical treatment of the subject. It explores the building of stochastic (statistical) models for time series and their use in important areas of application forecasting, model specification, estimation, modeling the effects of intervention events, and process control, among others. In addition to meticulous modifications in content and improvements in style, the new edition incorporates several new topics in an effort to modernize the subject matter. These topics include extensive discussions of multivariate time series, smoothing, likelihood function based on the state space model, autoregressive models, structural component models and deterministic seasonal components, and nonlinear and long memory models.
Автор: Douglas C. Montgomery,Cheryl L. Jennings,Murat Kul Название: Introduction to Time Series Analysis and Forecasting ISBN: 1118745116 ISBN-13(EAN): 9781118745113 Издательство: Wiley Рейтинг: Цена: 18208.00 р. Наличие на складе: Поставка под заказ.
Описание: Praise for the First Edition " [t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics.
Автор: Ignacio Rojas; H?ctor Pomares; Olga Valenzuela Название: Advances in Time Series Analysis and Forecasting ISBN: 3319557882 ISBN-13(EAN): 9783319557885 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- Part I: Analysis of Irregularly Sampled Time Series: Techniques, Algorithms and Case Studies.- Scientific Contributions.- Part II: Multi-scale Analysis of Univariate and Multivariate Time Series.- Scientific Contributions.- Part III: Linear and Non-linear Time Series Models.- Scientific Contributions.- Part IV: Advanced Time Series Forecasting Methods.- Scientific Contributions.- Part V: Applications in Time Series Analysis and Forecasting.- Scientific Contributions.- Author Index.
Описание: This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series.The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.
Автор: Arnold Zellner (Editor) Название: The Structural Econometric Time Series Analysis Approach ISBN: 0521187435 ISBN-13(EAN): 9780521187435 Издательство: Cambridge Academ Рейтинг: Цена: 7443.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book assembles previously published texts in the theory and application of the Structural Econometric Time Series Analysis (SEMTSA) approach. It provides a discussion of major considerations relating to the construction of econometric models that work well to explain economic phenomena, predict future outcomes and be useful for policy-making.
Автор: Jan G. De Gooijer Название: Elements of Nonlinear Time Series Analysis and Forecasting ISBN: 3319432516 ISBN-13(EAN): 9783319432519 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications.
Автор: Ignacio Rojas; H?ctor Pomares Название: Time Series Analysis and Forecasting ISBN: 3319287230 ISBN-13(EAN): 9783319287232 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Main Topics:
Time Series Analysis and Forecasting.- Advanced method and on-Line Learning in time series.- High Dimension and Complex/Big Data.- Forecasting in real problem.
Описание: In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyse economic and financial data on behalf of economic and financial institutions and to provide statistics.
Автор: Joseph K. Blitzstein, Jessica Hwang Название: Introduction to Probability, Second Edition ISBN: 1138369918 ISBN-13(EAN): 9781138369917 Издательство: Taylor&Francis Рейтинг: Цена: 11176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.
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