Give the interpretation of the ARMA model of the sugar prices. Derive the equation. ARIMA regression...
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Give the interpretation of the ARMA model of the sugar prices. Derive the equation. ARIMA regression Sample: 2 - 391 Log likelihood = 1039.621 Number of obs 390 Wald chi2 (6) 3664.86 Prob chi2 0.0000 OPG D. sugar Coef. Std. Err. Z P>|z [95% Conf. Interval] ARMA ar L1. 1.738648 .3632901 L2. -.757354 .6274176 L3. -.0969912 .3157903 4.79 0.000 -1.21 0.227 -0.31 0.759 1.026613 -1.98707 -.7159288 2.450684 .472362 .5219464 ma L1. -1.557445 L2. L3. .4312186 .2458973 .3599825 .5869925 .279828 -4.33 0.000 0.73 0.463 -2.262997 -.851892 -.7192657 1.581703 0.88 0.380 -.3025554 .79435 /sigma .0168249 .0002329 72.23 0.000 .0163684 .0172815 Note: The test of the variance against zero is one sided, and the two-sided confidence interval is truncated at zero. predict error, resid (1 missing value generated) summarize error Variable error Obs Mean Std. Dev. Min Max 390 -.000456 .0168521 -.1830644 .0901935 tsline error, yline (-.000456 ) Give the interpretation of the ARMA model of the sugar prices. Derive the equation. ARIMA regression Sample: 2 - 391 Log likelihood = 1039.621 Number of obs 390 Wald chi2 (6) 3664.86 Prob chi2 0.0000 OPG D. sugar Coef. Std. Err. Z P>|z [95% Conf. Interval] ARMA ar L1. 1.738648 .3632901 L2. -.757354 .6274176 L3. -.0969912 .3157903 4.79 0.000 -1.21 0.227 -0.31 0.759 1.026613 -1.98707 -.7159288 2.450684 .472362 .5219464 ma L1. -1.557445 L2. L3. .4312186 .2458973 .3599825 .5869925 .279828 -4.33 0.000 0.73 0.463 -2.262997 -.851892 -.7192657 1.581703 0.88 0.380 -.3025554 .79435 /sigma .0168249 .0002329 72.23 0.000 .0163684 .0172815 Note: The test of the variance against zero is one sided, and the two-sided confidence interval is truncated at zero. predict error, resid (1 missing value generated) summarize error Variable error Obs Mean Std. Dev. Min Max 390 -.000456 .0168521 -.1830644 .0901935 tsline error, yline (-.000456 )
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