New Introduction to Multiple Time Series Analysis

Author: Helmut Lütkepohl
Edition:
Publisher: Springer
Binding: Paperback
ISBN: 3540262393
Price:
You Save: 37%

New Introduction to Multiple Time Series Analysis

This is the new and totally revised edition of Lütkepohl’s classic 1991 work.New Introduction to Multiple Time Series Analysis review. 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. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economicsRead full reviews of New Introduction to Multiple Time Series Analysis.

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New Introduction to Multiple Time Series Analysis: Helmut L?tkepohl

http://okey-books.com/New-Introduction-to-Multiple-Time-Series-Analysis/p194134/

This reference work and graduate-level textbook deals with analyzing and forecasting multiple time series, considering a wide range of models and methods. It is based on the authorÂ's successful Introduction to Multiple Time Series Analysis, updated to include the state of the art and latest developments in the field. The book enables readers to perform their analyses in a competent and up-to-date manner, bridging the gap to the difficult technical literature on the topic.

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New Introduction To Multiple Time Series Analysis: Helmut L?tkepohl

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New Introduction to Multiple Time Series Analysis , ISBN-13: 9783540262398, ISBN-10: 3540262393

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Heavily revised version of author's: Introduction to multiple time series analysis, 1991.

http://www.langtoninfo.com/showitem.aspx?isbn=3540401725

New Introduction to Multiple Time Series Analysis Reviews

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. The book now includes new chapters on cointegration analysis, structural vector autoregressions, cointegrated VARMA processes and multivariate ARCH models. The book bridges the gap to the difficult technical literature on the topic. It is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it.