SAS/ETS 9 22 User''''''''s Guide 34 pot
SAS/ETS 9.22 User''''s Guide 34 pot
... 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 2836 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...
SAS/ETS 9.22 User''''s Guide 4 potx
... 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 ... with polynomial distributed
(Almon) lags. The PDLREG procedure includes the following features:
22 ✦ Chapter 2: Introduction
your own SAS programs in lowercase, uppercase, or a mixture of...
SAS/ETS 9.22 User''''s Guide 14 potx
... 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.
Similarl...
SAS/ETS 9.22 User''''s Guide 17 pot
... 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...
SAS/ETS 9.22 User''''s Guide 24 pot
... 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 with ... ;
FORECAST options ;
The PROC ARIMA and IDENTIFY statements are required.
PROC ARIMA Statement ✦ 227
Table 7.3 continued
Description Statement Option
specify moving-average starting values E...
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...
SAS/ETS 9.22 User''''s Guide 38 potx
... 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...
SAS/ETS 9.22 User''''s Guide 42 pot
... 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...
SAS/ETS 9.22 User''''s Guide 44 potx
... 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 21.0772644 HQC 190 .53 697 6
Durbin-Watson 1.3321 Regress ... Label
Intercept 1 -18.6582 34. 8101 -0.54 0. 599 3
gef 1 0.03 39 0.01 79 1. 89 0.07 69 Lagged Value of GE shares
gec 1 0.13 69 0.04 49 3.05 0.0076 Lagged Capit...
SAS/ETS 9.22 User''''s Guide 48 pot
... 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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