PROC IML 9.3 下运行出错，9.4 的大学版正常。

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各位， 以下CODE  9.3 出错， 9.4 正常， 求解？

1. proc iml;
   
2. /* Let X1, X2,...,Xd be binary variables, let
   
3.    p = (p1,p2,...,pd) the their expected values and let
   
4.    Delta be the d x d matrix of correlations.
   
5.    This function returns 1 if p and Delta are feasible for binary
   
6.    variables. The function also computes lower and upper bounds on the
   
7.    correlations, and returns them in LBound and UBound, respectively  */
   
8. 
   
9. start CheckMVBinaryParams(LBound, UBound, _p, Delta);
   
10.     p = rowvec(_p); q = 1 - p;              /* make p a row vector */
    
11.     d = ncol(p);                            /*number of variables */
    
12. 
    
13.     /* 1. check range of Delta; make sure p and Delta are feasible */
    
14.     PP = p`*p;  PQ = p`*q;
    
15.     QP = q`*p; QQ = q`*q;
    
16. 
    
17.     A = -sqrt(PP/QQ); B = -sqrt(QQ/PP);     /* matrices */
    
18.     LBound = choose(A>B,A,B);               /* elementwise max(A or B) */
    
19.     LBound[loc(I(d))] = 1;                  /* set diagonal to 1 */
    
20.     A = sqrt(PQ/QP); B = sqrt(QP/PQ);
    
21.     UBound = choose(A<B,A,B);               /*min(A or B)*/
    
22.     UBound[loc(I(d))] = 1;                  /*set diagonal to 1*/
    
23.     /*return 1 <==> specified means and correlations are feasible*/
    
24.     return( all(Delta >= LBound) & all(Delta <= UBound) );
    
25. finish;
    
26. 
    
27. 
    
28. 
    
29. /*Objective: Find correlation, rho, that is zero of this function.
    
30. Global variables:
    
31. pj = prob of success for binary var Xj
    
32. pk = prob of success for binary var Xk
    
33. djk = target correlation between Xj and Xk */
    
34. start MVBFunc(rho) global(pj, pk, djk);
    
35. Phi = probbnrm(quantile("Normal",pj), quantile("Normal",pk), rho);
    
36. qj = 1-pj; qk = 1-pk;
    
37. return(Phi - pj*pk - djk*sqrt(pj*qj*pk*qk));
    
38. finish;
    
39. 
    
40. 
    
41. start bisection(a, b);
    
42. dx = 1e-6; dy = 1e-4;
    
43. do i = 1 to 100; /** max iterations **/
    
44.    c = (a+b)/2;
    
45.    if abs(MVBFunc(c)) < dy | (b-a)/2 < dx then
    
46.       return(c);
    
47.    if MVBFunc(a)#MVBFunc(c) > 0 then a = c;
    
48.    else b = c;
    
49. end;
    
50. return (.); /** no convergence **/
    
51. finish;
    
52. 
    
53. 
    
54. start RandMVBinary(N, p, Delta) global(pj, pk, djk);
    
55. 
    
56.     /*1. Check parameters. Compute lower/upper bounds for all (j,k)*/
    
57. 
    
58.     if ^CheckMVBinaryParams(LBound, UBound, p, Delta) then do;
    
59.         print "The specified correlation is invalid." LBound Delta UBound;
    
60.         STOP;
    
61.     end;
    
62.     q = 1 - p;
    
63.     d = ncol(Delta); /*number of variables*/
    
64. 
    
65.     /*2. Construct intermediate correlation matrix by solving the
    
66.     bivariate CDF (PROBBNRM) equation for each pair of vars */
    
67.     R = I(d);
    
68.     do j = 1 to d-1;
    
69.     do k = j+1 to d;
    
70.     pj=p[j]; pk=p[k]; djk = Delta[j,k]; /*set global vars*/
    
71.     R[j,k] = bisection(LBound[j,k], UBound[j,k]);  /*pre-12.1， 9.3 SAS 需要运行这个*/
    
72. /*    R[j,k] = froot("MVBFunc", LBound[j,k]||UBound[j,k]);*/
    
73.     R[k,j] = R[j,k];
    
74.     end;
    
75.     end;
    
76. 
    
77.     /*3: Generate MV normal with mean 0 and covariance R*/
    
78.     X = RandNormal(N, j(1,d,0), R);                     
    
79. 
    
80.     /*4: Obtain binary variable from normal quantile*/
    
81.     do j = 1 to d;
    
82.     X[,j] = (X[,j] <= quantile("Normal", p[j]));         /*convert to 0/1*/
    
83.     end;
    
84.     return (X);
    
85. finish;
    
86. 
    
87. 
    
88. call randseed(1234);
    
89. p = {0.25 0.75 0.5};                     /*expected values of the X[j]*/
    
90. Delta = {  1 -0.1 -0.25,
    
91.                     -0.1 1 0.25,
    
92.                     -0.25 0.25 1 };                /*correlations between the X[j]*/
    
93. X = RandMVBinary(1000, p, Delta);        
    
94. 
    
95. /*compare sample estimates to parameters*/
    
96. mean = mean(X);
    
97. corr = corr(X);
    
98. print p, mean, Delta, corr[format=best6.];
    
99. 
    
100. quit;

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关键词：运行出错 ROC correlations intermediate respectively 大学

我这里没有报错，64位

SAS (r) Proprietary Software 9.3 (TS1M2 DBCS3060)

SAS (r) Proprietary Software 9.3 (TS1M0 DBCS3060)

ERROR: (execution) Matrix has not been set to a value.