SAS/ETS 9 22 User''''''''s Guide 13 pptx

SAS/ETS 9.22 User''''s Guide 13 pptx

SAS/ETS 9.22 User''''s Guide 13 pptx

... JUL90 135 .6 135 .0 15 New York JAN90 135 .1 . 16 New York FEB90 135 .3 135 .1 17 New York MAR90 136 .6 135 .3 18 New York APR90 137 .3 136 .6 19 New York MAY90 137 .2 137 .3 20 New York JUN90 137 .1 137 .2 21 ... JUN 199 1 ACTUAL 0 136 .000 38 JUN 199 1 FORECAST 0 136 .146 39 JUN 199 1 RESIDUAL 0 -0.146 40 JUL 199 1 ACTUAL 0 136 .200 41 JUL 199 1 FORECAST 0 136 .566 42 J...
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SAS/ETS 9.22 User''''s Guide 8 pptx

SAS/ETS 9.22 User''''s Guide 8 pptx

... 199 0 6 1 29. 9 2 199 0 7 130 .4 3 199 0 8 131 .6 4 199 0 9 132 .7 5 199 0 10 133 .5 6 199 0 11 133 .8 7 199 0 12 133 .8 8 199 1 1 134 .6 9 199 1 2 134 .8 10 199 1 3 135 .0 11 199 1 4 135 .2 12 199 1 5 135 .6 13 199 1 ... 01OCT 199 0 6 NOV 199 0 133 .8 11262 01NOV 199 0 7 DEC 199 0 133 .8 11 292 01DEC 199 0 8 JAN 199 1 134 .6 1132 3 01JAN 199 1 9 FEB 199 1 134 .8 1135 4...
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SAS/ETS 9.22 User''''s Guide 19 pptx

SAS/ETS 9.22 User''''s Guide 19 pptx

... restart update method of Powell ( 197 7) and Beale ( 197 2).  FR performs the Fletcher-Reeves update (Fletcher 198 7).  PR performs the Polak-Ribiere update (Fletcher 198 7).  CD performs a conjugate-descent ... approximation. The trust region method is implemented using Dennis, Gay, and Welsch ( 198 1), Gay ( 198 3), and Moré and Sorensen ( 198 3). The trust region method performs well fo...
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SAS/ETS 9.22 User''''s Guide 20 pptx

SAS/ETS 9.22 User''''s Guide 20 pptx

... Mei, H.H.W. ( 197 9), “Two New Unconstrained Optimization Algorithms Which Use Function and Gradient Values,” J. Optim. Theory Appl., 28, 453–482. Dennis, J.E. and Schnabel, R.B. ( 198 3), Numerical ... E.M.L. ( 197 2), “A Derivation of Conjugate Gradients,” in Numerical Methods for Nonlinear Optimization, ed. F.A. Lootsma, London: Academic Press. Dennis, J.E., Gay, D.M., and Welsch, R.E. ( 1...
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SAS/ETS 9.22 User''''s Guide 33 pptx

SAS/ETS 9.22 User''''s Guide 33 pptx

... Technometrics, 22, 3 89 396 . Kohn, R. and Ansley, C. ( 198 5), “Efficient Estimation and Prediction in Time Series Regression Models,” Biometrika, 72, 3, 694 – 697 . Ljung, G. M. and Box, G. E. P. ( 197 8), “On ... Models,” JASA, 79 (385), 84 96 . Tsay, R. S. and Tiao, G. C. ( 198 5), “Use of Canonical Analysis in Time Series Model Identification,” Biometrika, 72 (2), 299 –315. Woodfield, T....
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SAS/ETS 9.22 User''''s Guide 52 pptx

SAS/ETS 9.22 User''''s Guide 52 pptx

... 1 1 JAN 198 22 090 255 24368 -227 8 -9. 348 1 1 1 FEB 223 26830 217 20104 6726 33.456 1 1 1 MAR 1 19 14020 210 194 05 -5385 -27.751 1 1 1 QTR1 540 6 294 0 682 63877 -93 7 -1.467 1 1 1 APR 82 98 60 162 ... 16374 -6514 - 39. 783 1 1 1 MAY 180 2133 0 67 6325 15005 237.233 1 1 1 JUN 183 21060 124 12333 8727 70.761 1 1 1 QTR2 445 5225 0 353 35032 17218 49. 1 49 1 1 1 JUL 194 23210 99 10310...
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SAS/ETS 9.22 User''''s Guide 78 pptx

SAS/ETS 9.22 User''''s Guide 78 pptx

... group of a specified number of input observations. For example, if you specify the option FACTOR= (13: 2), 13 equally spaced output observations are interpolated from each pair of input observations. You ... spaced points in time. proc expand data=a out=b; run; Refer to the section “Missing Values” on page 792 for further information. Requesting Different Interpolation Methods By default, a...
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SAS/ETS 9.22 User''''s Guide 92 pptx

SAS/ETS 9.22 User''''s Guide 92 pptx

... 0.051424 137 741.07 0.00 2 108561.77 0.0 5221 2 130 397 .88 130 788.65 3 118182. 19 0.087784 161810.00 75 798 . 19 4 107015.58 0.053231 13 195 5 .90 125011.88 5 10 790 6.61 0.052107 130 242.56 138 063.41 6 578 39. 44 ... 578 39. 44 0.051424 137 741.07 0.00 7 240325. 49 0.053247 12 198 0 .94 0.00 8 138 858.08 0.0860 79 161536.44 0.00 9 237647.82 0.054528 124700 .22 0.00 10 2828...
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SAS/ETS 9.22 User''''s Guide 105 pptx

SAS/ETS 9.22 User''''s Guide 105 pptx

... Estimates Approx Approx Term Estimate Std Err t Value Pr > |t| Label Join point 12.7504 1.2785 9. 97 <.0001 x0 plateau 0.777516 0.0123 63.10 <.0001 a + b * x0 + c * x0 ** 2 EXOGENOUS Statement EXOGENOUS ... missing observations, the Durbin-Watson statistic calculated is d 0 as suggested by Savin and White ( 197 8). This is the usual Durbin-Watson computed by ignoring the gaps. Savin...
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SAS/ETS 9.22 User''''s Guide 120 pptx

SAS/ETS 9.22 User''''s Guide 120 pptx

... data=sashelp.citimon; parameters a 0.010708 b -0.4788 49 c 0 .92 9304; lhur= 1/(a * ip) + b + c * lag(lhur) ; solve lhur / out=sim dynamic stats theil; range date to '01nov91'd; run; The STATS output in ... THEIL output in Figure 18. 79 are generated. Figure 18.78 STATS Output The MODEL Procedure Dynamic Single-Equation Simulation Solution Range DATE = FEB 198 0 To NOV 199 1 Descr...
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