Mathematics, 25.04.2020 04:19 olgapagan3173
5.16\.\* In Example 3.14 we fit the model Rt = b0 + b1St6 + b2Dt6 + b3Dt6 St6 + wt, where Rt is Recruitment, St is SOI, and Dt is a dummy variable that is 0 if St < 0 and 1 otherwise. However, residual analysis indicated that the residuals are not white noise. (a) Plot the ACF and PACF of the residuals and discuss why an AR(2) model might be appropriate. (b) Fit the dummy variable regression model assuming that the noise is correlated noise and compare your results to the results of Example 3.14 (compare the estimated parameters and the corresponding standard errors). (c) Now fit a seasonal model for the noise in the previous part.
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5.16\.\* In Example 3.14 we fit the model Rt = b0 + b1St6 + b2Dt6 + b3Dt6 St6 + wt, where Rt is Recr...
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