SAS/ETS 9 22 User''''''''s Guide 28 pot

... var=ylog; estimate p=2; forecast lead=10 out=out; run; data out; set out; y = exp( ylog ); l95 = exp( l95 ); u95 = exp( u95 ); forecast = exp( forecast + std * std/2 ); run; Specifying Series Periodicity ... quantities ı and Ä are efficiently computed by a method described in de Jong and Penzer ( 199 8); see also Kohn and Ansley ( 198 5). Modeling in the Presence of Outliers In practice, model...

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... sources of information about SAS/ETS software. Accessing the SAS/ETS Sample Library The SAS/ETS Sample Library includes many examples that illustrate the use of SAS/ETS software, including the ... combination of coefficients, within a single model or across equations  tests for any linear hypothesis, for the parameters of a single model or across equations Linear Systems Simulation Th...

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... cpi 1 JUN90 114.3 . 2 JUL90 114.5 . 3 AUG90 116.5 131.6 4 SEP90 118.4 132.7 5 OCT90 120.8 133.5 6 NOV90 120.1 133.8 7 DEC90 118.7 133.8 8 JAN91 1 19. 0 134.6 9 FEB91 117.2 134.8 10 MAR91 116.2 ... the intervals January 1, 196 0, February 1, 196 1, March 1, 196 2, and so forth, and the intervals December 1, 195 9, November 1, 195 8, and so on before the base date January 1, 196 0. Similarly,...

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... variable &DFTEST. If the p-value is less than 0.01 or larger than 0 .99 , the macro variable &DFTEST is set to 0.01 or 0 .99 , respectively. (The same value is given in the macro variable &DFPVALUE ... variable &DFPVALUE. If the p-value is less than 0.01 or larger than 0 .99 , the macro variable &DFPVALUE is set to 0.01 or 0 .99 , respectively. Minimum Observations The min...

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... PLOTS= Options to Specify Parameter Values specify autoregressive starting values ESTIMATE AR= 228 ✦ Chapter 7: The ARIMA Procedure specifications appear in the PROC ARIMA and IDENTIFY statements, ... options. ALL produces all plots appropriate for the particular analysis. PROC ARIMA Statement ✦ 2 29 NONE suppresses all plots. SERIES(< series-plot-options > ) produces plots associated...

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... Estimates SSE 97 .71 1226 DFE 33 MSE 2 .96 095 Root MSE 1.72074 SBC 142.3 697 87 AIC 1 39. 2 590 91 MAE 1. 299 493 85 AICC 1 39. 634 091 MAPE 8. 192 283 6 HQC 140.33 290 3 Regress R-Square 0 .91 09 Total R-Square 0 .91 09 Miscellaneous ... Least Squares Estimates SSE 214 .95 34 29 DFE 34 MSE 6. 3221 6 Root MSE 2.514 39 SBC 173.6 591 01 AIC 170. 492 063 MAE 2.0 190 3356 AICC 170.855 699...

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... default. TEST=LM produces a Lagrange multiplier test for heteroscedasticity. The null hypothesis is homoscedas- ticity; the alternative hypothesis is heteroscedasticity of the form specified by the HETERO statement. ... supports a TEST statement for linear hypothesis tests. The syntax of the TEST statement is TEST equation , . . . , equation / option ; The TEST statement tests hypotheses about...

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... model. Under the null hypothesis, the Chow test statistic has an F distribution with k and .n 1 C n 2  2k/ degrees of freedom, where k is the number of elements in ˇ. Chow ( 196 0) suggested another ... P= option. 404 ✦ Chapter 8: The AUTOREG Procedure Wong and Li’s Test for ARCH Disturbances Wong and Li ( 199 5) propose a rank portmanteau statistic to minimize the effect of the existence of...

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... 0 .221 867 -2.08 Algorithm converged. Maximum Likelihood Estimates SSE 102 29. 2303 DFE 16 MSE 6 39. 326 89 Root MSE 25 .28 491 SBC 193 .738877 AIC 1 89. 75 594 7 MAE 18.0 892 426 AICC 192 . 4226 14 MAPE 21. 097 8407 ... continued Yule-Walker Estimates SSE 10238. 295 1 DFE 16 MSE 6 39. 893 44 Root MSE 25. 296 12 SBC 193 .742 396 AIC 1 89. 7 594 67 MAE 18.0715 195 AICC 192 .426133 MAPE 21.0...

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... 31JAN 198 9 95 000 10500 2000 6500 B 31JAN 198 9 668000 112000 5600 90 000 C 31JAN 198 9 105000 6800 90 00 18500 A 28FEB 198 9 91 000 8200 190 0 12000 B 28FEB 198 9 602000 99 000 5500 86000 C 28FEB 198 9 96 000 ... 6500 2 B 31JAN 89 668000 112000 5600 90 000 3 C 31JAN 89 105000 6800 90 00 18500 4 A 28FEB 89 91000 8200 190 0 12000 5 B 28FEB 89 602000 99 000 5500 86000 6 C 28FEB 89...

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