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This book is a practical guide to selecting and applying the most appropriate time series model and analysis of data sets using EViews. After introducing EViews workfiles and how to carry… Plus…

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Time Series Data Analysis Using Eviews - nouveau livre

ISBN: 9780470823675

This book is a practical guide to selecting and applying the most appropriate time series model and analysis of data sets using EViews. After introducing EViews workfiles and how to carry… Plus…

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Time Series Data Analysis Using Eviews - nouveau livre

ISBN: 9780470823675

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Time Series Data Analysis Using EViews by I. Gusti Ngurah Agung Hardcover | Indigo Chapters
Auteur:
Titre:
ISBN:

9780470823675


This book is a practical guide to selecting and applying the most appropriate time series model and analysis of data sets using EViews. After introducing EViews workfiles and how to carry out descriptive data analysis, the book goes on to describe various models in detail (continuous growth, discontinuous growth, seemingly causal models, special cases of regression models, ARCH and GARCH models), all illustrated with a rich variety of examples and accompanied by helpful notes. Additional testing hypotheses are also explored and finally extension to a general form of nonlinear time series model is examined. Designed as a special guide for students and less experienced researchers it is a perfect complement to more theoretical books presenting statistical or econometric models for time series data.

Informations détaillées sur le livre - Time Series Data Analysis Using EViews by I. Gusti Ngurah Agung Hardcover | Indigo Chapters


EAN (ISBN-13): 9780470823675
ISBN (ISBN-10): 0470823674
Version reliée
Livre de poche
Date de parution: 2009
Editeur: I. Gusti Ngurah Agung
609 Pages
Poids: 1,021 kg
Langue: eng/Englisch

Livre dans la base de données depuis 2007-08-24T03:11:24+02:00 (Paris)
Page de détail modifiée en dernier sur 2024-03-24T02:20:25+01:00 (Paris)
ISBN/EAN: 9780470823675

ISBN - Autres types d'écriture:
0-470-82367-4, 978-0-470-82367-5
Autres types d'écriture et termes associés:
Auteur du livre: ign, giusta, john wiley sons, gusti ngurah
Titre du livre: data analysis, using eviews, only time will tell, data net ufo, this time different, little time, take your time, our time, once upon time never comes again, taken out time, four time, time goes, doing time, how tell time, time was, time brief, time series analysis

Données de l'éditeur

Titre: Time Series Data Analysis Using EViews
Editeur: John Wiley & Sons
632 Pages
Date de parution: 2009-02-17
Poids: 0,916 kg
Langue: Anglais
122,00 € (DE)
No longer receiving updates
162mm x 235mm x 33mm

BB; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Econometrics; Economics; Finanz- u. Wirtschaftsstatistik; Ökonometrie; Statistics; Statistics for Finance, Business & Economics; Statistik; Time Series; Volkswirtschaftslehre; Zeitreihen; Zeitreihenanalyse; Ökonometrie; Finanz- u. Wirtschaftsstatistik; Zeitreihen; Ökonometrie und Wirtschaftsstatistik

Contents Preface List Of Tables List Of Figures Chapter 1: Eviews Workfile And Descriptive Data Analysis 1.1 What Is The Eviews Workfile? 1.2 Basic Options In Eviews 1.3 Creating A Workfile 1.4 Illustrative Data Analysis 1.5 Special Notes And Comments 1.6 Statistics As A Sample Space Chapter 2: Continuous Growth Models 2.1 Introduction 2.2 Classical Growth Models 2.3 Autoregressive Growth Models 2.4. Residual Tests 2.5 Bounded Autoregressive Growth Models 2.6 Lagged Variables Or Autoregressive Growth Models 2.7 Polynomial Growth Model 2.8. Growth Models With Exogenous Variables 2.9. A Taylor Series Approximation Model 2.10 Alternative Univariate Growth Models 2.11 Multivariate Growth Models 2.12. Multivariate Ar(P) Glm With Trend 2.13. Generalized Multivariate Models With Trend 2.14 Special Notes And Comments 2.15 Alternative Multivariate Models With Trend 2.16. Generalized Multivariate Models With Time-Related-Effects Chapter 3: Discontinuous Growth Models 3.1 Introduction 3.2. Piecewise Growth Models 3.3 Piecewise S-Shape Growth Models 3.4 Two-Pieces Polynomial Bounded Growth Models 3.5 Discontinuous Translog Linear Ar(1) Growth Models. 3.6 Alternative Discontinuous Growth Models 3.7 Stability Test 3.8 Generalized Discontinuous Models With Trend 3.9 General Two-Pieces Models With Time-Related Effects 3.10. Multivariate Models By States And Time Periods 10.2 Not Recommended Models Chapter 4: Seemingly Causal Models 4.1 Introduction 4.2 Statistical Analysis Based On Single Time Series 4.3 Bivariate Seemingly Causal Models 4.4 Trivariate Seemingly Causal Models 4.5 System Equations Based On Trivariate Time Series 4.6. General System Of Equations 4.7 Seemingly Causal Models With Dummy Variables 4.8. General Discontinuous Seemingly Causal Models 4.9. Additional Selected Seemingly Causal Models 4.10. Final Notes In Developing Models Chapter 5: Special Cases Of Regression Models 5.1. Introduction 5.2 Specific Cases Of Growth Curve Models 5.3 Seemingly Causal Models 5.4 Lagged Variable Models And The Autoregresive Model 5.5 Cases Based On The Us Domestic Price Of Copper 5.6 Return Rate Models 5.7 Cases Based On The Basics Workfile Chapter 6: Var And System Estimation Methods 6.1. Introduction 6.2 The Var Models 6.3 The Vector Error Correction Models 6.4 Special Notes And Comments Chapter 7: Instrumental Variables Models 7.1. Introduction 7.2 Should We Apply Instrumental Models? 7.3 Residual Analysis In Developing Instrumental Models 7.4 System Equation With Instrumental Variables 7.3 Selected Cases Based On The Us_Dpoc Data 7.6 Intrumentals Models With Time-Related-Effects 7.3 Intrumental Seemingly Causal Models 7.8 Multivariate Instrumental Models, Based On The Us_Dpoc 7.9. Further Extension Of The Instrumental Models Chapter 8: Arch Models 8.1 Introduction 8.2 The Options Of Arch Models 8.3 Simple Arch Models 8.4. Acrh Models With Exogenous Variables 8.5 Alternative Garch Variance Series Chapter 9: Additional Testing Hypotheses 9.1. Introduction 9.2. The Unit Root Tests 9.3 The Omitted Variables Tests 9.4. Redundant Variables Test (Rv-Test) 9.5 Non-Nested Test (Nn-Test) 9.6 The Ramsey'S Reset Test Chapter 10: Nonlinear Least Squares Models 10.1 Introduction 10.2 Classical Growth Models 10.3 Generalized Cobb-Douglas Models 10.3 Generalized Ces Models 10.4 Special Notes And Comments 10.5 Other Nls Models Chapter 11: Nonparametric Estimation Methods 11.1 What Is The Nonparamtric Data Analysis 11.2 Basic Moving Average Estimates 11.3 Measuring The Best Fit Model 11.4. Advanced Moving Average Models 11.5. Nonparametric Regression Based On Time Series 11.6 The Local Polynomial Kernel Fit Regression 11.7 Nonparametric Growth Models
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