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New Introduction to Multiple Time Series Analysis

New Introduction to Multiple Time Series Analysis
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
Total Pages: 792
Release: 2007-07-26
Genre: Business & Economics
ISBN: 9783540262398

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This is the new and totally revised edition of Lütkepohl’s classic 1991 work. 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.


Introduction to Multiple Time Series Analysis

Introduction to Multiple Time Series Analysis
Author: Helmut Lütkepohl
Publisher: Springer Science & Business Media
Total Pages: 556
Release: 2013-04-17
Genre: Business & Economics
ISBN: 3662026910

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Introduction to Multiple Time Series Analysis

Introduction to Multiple Time Series Analysis
Author: Helmut Lütkepohl
Publisher: Springer
Total Pages: 546
Release: 2014-03-12
Genre: Business & Economics
ISBN: 9783662026922

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Introduction to Modern Time Series Analysis

Introduction to Modern Time Series Analysis
Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
Total Pages: 288
Release: 2008-08-27
Genre: Business & Economics
ISBN: 9783540687351

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This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.


Introduction to Multiple Time Series Analysis

Introduction to Multiple Time Series Analysis
Author: Helmut Lütkepohl
Publisher: Springer
Total Pages: 0
Release: 1993
Genre: Business & Economics
ISBN: 9783642616952

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This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book 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 this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.


Forecasting: principles and practice

Forecasting: principles and practice
Author: Rob J Hyndman
Publisher: OTexts
Total Pages: 380
Release: 2018-05-08
Genre: Business & Economics
ISBN: 0987507117

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Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.


Multivariate Time Series Analysis

Multivariate Time Series Analysis
Author: Ruey S. Tsay
Publisher: John Wiley & Sons
Total Pages: 414
Release: 2013-11-11
Genre: Mathematics
ISBN: 1118617754

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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.


Spectral Analysis of Time-series Data

Spectral Analysis of Time-series Data
Author: Rebecca M. Warner
Publisher: Guilford Press
Total Pages: 244
Release: 1998-05-22
Genre: Social Science
ISBN: 9781572303386

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This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.


Forecasting, Structural Time Series Models and the Kalman Filter

Forecasting, Structural Time Series Models and the Kalman Filter
Author: Andrew C. Harvey
Publisher: Cambridge University Press
Total Pages: 574
Release: 1990
Genre: Business & Economics
ISBN: 9780521405737

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A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.