03048nam 2200685Ia 450 991101982580332120251116163323.0978661238217897811181763061118176308978128238217612823821799780470823699047082369097804708236820470823682(CKB)1000000000799379(EBL)479876(OCoLC)609854707(SSID)ssj0000366795(PQKBManifestationID)11278621(PQKBTitleCode)TC0000366795(PQKBWorkID)10418407(PQKB)11282859(MiAaPQ)EBC479876(Perlego)1010149(UkBuK)968009(EXLCZ)99100000000079937920080807d2009 uy 0engur|n|---|||||txtccrTime series data analysis using EViews /I Gusti Ngurah Agung1Wiley20111 online resource (634 p.)Statistics in practice Time series data analysis using EViews Description based upon print version of record.9780470823675 0470823674 Includes bibliographical references and index.TIME SERIES DATA ANALYSIS USING EVIEWS; Contents; Preface; 1 EViews workfile and descriptive data analysis; 2 Continuous growth models; 3 Discontinuous growth models; 4 Seemingly causal models; 5 Special cases of regression models; 6 VAR and system estimation methods; 7 Instrumental variables models; 8 ARCH models; 9 Additional testing hypotheses; 10 Nonlinear least squares models; 11 Nonparametric estimation methods; Appendix A: Models for a single time series; Appendix B: Simple linear models; Appendix C: General linear models; Appendix D: Multivariate general linear models; ReferencesIndexDo you want to recognize the most suitable models for analysis of statistical data sets? This book provides a hands-on practical guide to using the most suitable models for analysis of statistical data sets using EViews - an interactive Windows-based computer software program for sophisticated data analysis, regression, and forecasting - to define and test statistical hypotheses. Rich in examples and with an emphasis on how to develop acceptable statistical models, Time Series Data Analysis Using EViews is a perfect complement to theoretical books presenting statistical or econometTime-series analysisEconometric modelsTime-series analysis.Econometric models.519.22519.5/5Agung I Gusti Ngurah614603MiAaPQMiAaPQMiAaPQBOOK9911019825803321Time series data analysis using eviews43621UNINA