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dmclerra@fhcrc.org
Dear Dale McLerran,
First of all, thank you very much for your nice illustrative e-mail
which was very helpful for a SAS newbie like me.
However, i had a little problem: i could not get Draper and Smith's
parameter estimates (1.2850000000, 0.0408333300, -0.024404760,
-0.013636360, 0.0022077920, 0.0013461540, 0.0003787879) directly from
SAS out put. [but i calculated and found that SAS estimates /
SS(respective column from the design matrix) gives the correct result
- well, except for the intercept term]. Can you please tell me how to
obtain the Draper and Smith's parameter estimates directly from SAS
output?
_____________________________
i used the following code:
_____________________________
title 'PROC ORTHOREG used with drsm data';
data drsm;
input Y X;
Year=X-1956;
datalines;
0.93 1957
0.99 1958
1.11 1959
1.33 1960
1.52 1961
1.60 1962
1.47 1963
1.33 1964
;
run;
proc iml;
use drsm;
read all var {X} into year;
read all var {y} into y; /* return orthogonal polynomial
design matrix of order 6 */
x = orpol(year-1956,6); /* Labels to use for design matrix */
order = {"Intercept", "1st order", "2nd order", "3rd order",
"4th order", "5th order", "6th order"};
/* Fit regression */
run regress(x,y,order,,,,);
ds_ssq = {8, 168, 168, 264, 616, 2184, 264};
x_new = fuzz(x`#sqrt(ds_ssq))`;
print x_new;
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and the out put was:
_____________________________
PROC ORTHOREG used with drsm data
1
07:23
NAME B STDB T
PROBT
Intercept 3.6345289 0.0116074 313.12147
0.0020331
1st order 0.5292605 0.0116074 45.596783
0.0139597
2nd order -0.316322 0.0116074 -27.25172
0.0233502
3rd order -0.221565 0.0116074 -19.08821
0.033321
4th order 0.054796 0.0116074 4.7207748
0.1328905
5th order 0.0629102 0.0116074 5.4198309
0.1161549
6th order 0.0061546 0.0116074 0.5302281
0.6896245
Covariance of Estimates
COVB Intercept 1st order 2nd order 3rd order 4th order
5th order 6th order
Intercept 0.0001 36E-21 -6E-20 12E-20 -3E-19
52E-20 -2E-18
1st order 36E-21 0.0001 14E-20 -2E-19 46E-20
-1E-18 29E-19
2nd order -6E-20 14E-20 0.0001 39E-20 -8E-19
17E-19 -5E-18
3rd order 12E-20 -2E-19 39E-20 0.0001 13E-19
-3E-18 86E-19
4th order -3E-19 46E-20 -8E-19 13E-19 0.0001
59E-19 -2E-17
5th order 52E-20 -1E-18 17E-19 -3E-18 59E-19
0.0001 39E-18
6th order -2E-18 29E-19 -5E-18 86E-19 -2E-17
39E-18 0.0001
Correlation of Estimates
CORRB Intercept 1st order 2nd order 3rd order 4th order
5th order 6th order
Intercept 1 27E-17 -4E-16 91E-17 -2E-15
39E-16 -1E-14
1st order 27E-17 1 1E-15 -2E-15 34E-16
-8E-15 22E-15
2nd order -4E-16 1E-15 1 29E-16 -6E-15
13E-15 -4E-14
3rd order 91E-17 -2E-15 29E-16 1 97E-16
-2E-14 64E-15
4th order -2E-15 34E-16 -6E-15 97E-16 1
43E-15 -1E-13
5th order 39E-16 -8E-15 13E-15 -2E-14 43E-15
1 29E-14
6th order -1E-14 22E-15 -4E-14 64E-15 -1E-13
29E-14 1
X_NEW
1 -7 7 -7 7 -7
1
1 -5 1 5 -13 23
-5
1 -3 -3 7 -3 -17
9
1 -1 -5 3 9 -15
-5
1 1 -5 -3 9 15
-5
1 3 -3 -7 -3 17
9
1 5 1 -5 -13 -23
-5
1 7 7 7 7 7
1
Thank you very much for your kind support.
_______________________
Mohammad Ehsanul Karim <wildscop@yahoo.com>
Institute of Statistical Research and Training
University of Dhaka, Dhaka- 1000, Bangladesh
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