Testing for a Unit Root in Time Series Regression PDF Download
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Author: Phillips, Peter C. B
Publisher: Montréal : Dép. de science économique, Université de Montréal
ISBN: 9782920857209
Category :
Languages : en
Pages : 31
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Book Description
Author: Phillips, Peter C. B
Publisher: Montréal : Dép. de science économique, Université de Montréal
ISBN: 9782920857209
Category :
Languages : en
Pages : 31
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Book Description
Author: Wayne A. Fuller
Publisher: John Wiley & Sons
ISBN: 0470317752
Category : Mathematics
Languages : en
Pages : 734
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Book Description
The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.
Author: Pierre Perron
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: G. S. Maddala
Publisher: Cambridge University Press
ISBN: 9780521587822
Category : Business & Economics
Languages : en
Pages : 528
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Book Description
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Author: Badi H. Baltagi
Publisher: Elsevier
ISBN: 0762306882
Category : Business & Economics
Languages : en
Pages : 351
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Book Description
In the 16th Edition of Advances in Econometrics we present twelve papers discussing the current interface between Marketing and Econometrics. The authors are leading scholars in the fields and introduce the latest models for analysing marketing data. The papers are representative of the types of problems and methods that are used within the field of marketing. Marketing focuses on the interaction between the firm and the consumer. Economics encompasses this interaction as well as many others. Economics, along with psychology and sociology, provides a theoretical foundation for marketing.
Author: Pierre Perron
Publisher:
ISBN: 9789813237896
Category : Econometrics
Languages : en
Pages :
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Book Description
Part I. Unit roots and trend breaks -- Part II. Structural change
Author: Constantin Colonescu
Publisher: Lulu.com
ISBN: 1387473611
Category : Business & Economics
Languages : en
Pages : 278
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Book Description
This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.
Author: Dr. Avishek Pal
Publisher: Packt Publishing Ltd
ISBN: 178829419X
Category : Computers
Languages : en
Pages : 238
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Book Description
Step by Step guide filled with real world practical examples. About This Book Get your first experience with data analysis with one of the most powerful types of analysis—time-series. Find patterns in your data and predict the future pattern based on historical data. Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide Who This Book Is For This book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods. What You Will Learn Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project Develop an understanding of loading, exploring, and visualizing time-series data Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series Take advantage of exponential smoothing to tackle noise in time series data Learn how to use auto-regressive models to make predictions using time-series data Build predictive models on time series using techniques based on auto-regressive moving averages Discover recent advancements in deep learning to build accurate forecasting models for time series Gain familiarity with the basics of Python as a powerful yet simple to write programming language In Detail Time Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python. The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python. The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python. Style and approach This book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.
Author: K. Patterson
Publisher: Springer
ISBN: 1137003316
Category : Business & Economics
Languages : en
Pages : 586
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Book Description
Testing for a Unit Root is now an essential part of time series analysis but the literature on the topic is so large that knowing where to start is difficult even for the specialist. This book provides a way into the techniques of unit root testing, explaining the pitfalls and nonstandard cases, using practical examples and simulation analysis.
Author: Bernhard Pfaff
Publisher: Springer Science & Business Media
ISBN: 0387759670
Category : Business & Economics
Languages : en
Pages : 193
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Book Description
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
