Problem of autocorrelation arises if the assumption of the Classical Linear Regression Model that the errors terms are not autocorrelated is violated. As a consequence, the usual t, F, and χ2 tests cannot be legitimately applied. This text uses various econometric approaches to critically observe the associated problems. Graphical method; Durbin-Watson method; Breush-Godfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of first-difference, based on Durbin-Watson d-statistic and the dynamic forecasting techniques were used. The result gave a significantly reduced estimated autocorrelation coefficient. This improves the efficiency of the forecast and the use of various statistics in making inference.
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ADETUNJI, ADEMOLA ABIODUN was born in Osogbo, Osun State, Nigeria some three decades ago.He is a young and ambitious scholar with a number of academic scholarships and publications to his credit.He is an aspiring researcher with major interest in Econometrics and Categorical Data Analysis.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Problem of autocorrelation arises if the assumption of the Classical Linear Regression Model that the errors terms are not autocorrelated is violated. As a consequence, the usual t, F, and ¿2 tests cannot be legitimately applied. This text uses various econometric approaches to critically observe the associated problems. Graphical method; Durbin-Watson method; Breush-Godfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of first-difference, based on Durbin-Watson d-statistic and the dynamic forecasting techniques were used. The result gave a significantly reduced estimated autocorrelation coefficient. This improves the efficiency of the forecast and the use of various statistics in making inference. 88 pp. Englisch. Codice articolo 9783659309458
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Adetunji AdemolaADETUNJI, ADEMOLA ABIODUN was born in Osogbo, Osun State, Nigeria some three decades ago.He is a young and ambitious scholar with a number of academic scholarships and publications to his credit.He is an aspiring rese. Codice articolo 5147509
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Taschenbuch. Condizione: Neu. Neuware -Problem of autocorrelation arises if the assumption of the Classical Linear Regression Model that the errors terms are not autocorrelated is violated. As a consequence, the usual t, F, and ¿2 tests cannot be legitimately applied. This text uses various econometric approaches to critically observe the associated problems. Graphical method; Durbin-Watson method; Breush-Godfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of first-difference, based on Durbin-Watson d-statistic and the dynamic forecasting techniques were used. The result gave a significantly reduced estimated autocorrelation coefficient. This improves the efficiency of the forecast and the use of various statistics in making inference.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Codice articolo 9783659309458
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Problem of autocorrelation arises if the assumption of the Classical Linear Regression Model that the errors terms are not autocorrelated is violated. As a consequence, the usual t, F, and ¿2 tests cannot be legitimately applied. This text uses various econometric approaches to critically observe the associated problems. Graphical method; Durbin-Watson method; Breush-Godfrey method; and The Runs Test were used to detect existence of autocorrelation among residuals of econometric data. In correcting autocorrelation, the method of first-difference, based on Durbin-Watson d-statistic and the dynamic forecasting techniques were used. The result gave a significantly reduced estimated autocorrelation coefficient. This improves the efficiency of the forecast and the use of various statistics in making inference. Codice articolo 9783659309458
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