Hello. I am trying to approximate a 36 points series to a quaterly data of 9 quarters. The objetive here is that the optimized series of 36 points fits the goal for those 9 quarters with minimal error while being a smooth and monotonous function. I was trying to use the following code: proc iml; /* Step 1: Define Bayes values from macro variables */ bayes = { &bayes1, &bayes2, &bayes3, &bayes4, &bayes5, &bayes6, &bayes7, &bayes8, &bayes9 }; /* Step 2: Define initial guess (e.g., from macro variables &pd1–&pd36) */ PD_ini = { &PD1, &PD2, &PD3, &PD4, &PD5, &PD6, &PD7, &PD8, &PD9, &PD10, &PD11, &PD12, &PD13, &PD14, &PD15, &PD16, &PD17, &PD18, &PD19, &PD20, &PD21, &PD22, &PD23, &PD24, &PD25, &PD26, &PD27, &PD28, &PD29, &PD30, &PD31, &PD32, &PD33, &PD34, &PD35, &PD36 }; PD_init=t(PD_ini); /* Step 3: Define the objective function */ start objetive(pd) global(bayes); S = j(1, 36, .); CumPD = j(1, 36, .); S[1] = 1 - pd[1]; CumPD[1] = 1 - S[1]; do t = 2 to 36; S[t] = S[t-1] * (1 - pd[t]); CumPD[t] = 1 - S[t]; end; obj = 0; do i = 0 to 8; t = i * 3 + 1; /* Corresponds to months 0, 3, ..., 24 */ condPD = (CumPD[t+12] - CumPD[t]) / S[t]; err = (condPD - bayes[i+1]) * 100; obj = obj + err##2; end; return (obj); finish; /* Step 4: Call optimizer */ optn = {0}; /* 0 = minimize */ call nlpqn(rc, result, "objetive", initPD, optn); /* Step 5: Output results */ print rc result; quit; But I keep getting this error: 74 ! /* 0 = minimize */ 75 call nlpqn(rc, result, "objetive", initPD, optn); ERROR: (execution) Matrix has not been set to a value. I have also tried to use the initial matrixes as constants but it didnt work either. Ex: bayes = {0.0002639011, 0.0003372667, 0.0004005217, 0.0004619689, 0.0005238603, 0.0005852403, 0.000645032, 0.0007037884, 0.0007612079 and PD_ini = j(1,36,0.01); Note: My base SAS software is 9.4 and the IML is For SAS/IML 15.2. Can someone give some pointers or some help. I would apreciate it 😃
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