About BY2

BY2 · ‎11-26-2020

Is it possible to use OR instead of Max for the array?

BY2 · ‎11-25-2020

NO AAA AAA_L1 AAA_L2 AAA_L3 BBB BBB_L1 BBB_L2 BBB_L3 AAA_I BBB_I 1 0.1 -0.1 1 1 2 -0.1 0.1 0 0 3 -1 -0.1 0 1 data want; set test; if AAA > 0 OR AAA_L1>0 OR AAA_L2>0 OR AAA_L3>0 THEN AAA_I = 1;ELSE AAA_I = 0; If BBB < 0 OR BBB_L1<0 OR BBB_L2<0 OR BBB_L3<0 THEN BBB_I = 0;ELSE BBB_I = 1; run; Is there any way that could cut short the code as i have more than 50 similar variables as shown above. Thank you for your help.

BY2 · ‎08-05-2020

Yes, that is correct. Please proceed.

BY2 · ‎08-03-2020

Hi, cy1 to cy9 should be some smaller values instead of 6 digits number. Please take note of the difference of colC and col_c, hope you didnt use the wrong variable. Apologies for the confusion, let me explain sumproduct by using one of the example below: 1. In this example, In order to obtain cy1, will need to sum up every row of (col_c * colE1). Please refer below: row1: col_c * colE1 row2: col_c * colE1 ... ... (do the same till the last row and then sum all of them up will be the sumproduct of col_c * colE1). 2. However, it is a little different for the equation of lm where it is the sumproduct of cy1-cy9. Please refer below: row1: cy1*cy1 + cy2*cy2 + cy3*cy3 + .... + cy9*cy9 Note: lm should be same across all observation. Thank you.

BY2 · ‎07-28-2020

Yes, Once Y is solved from getting sum of col_ML = sum of col_IL. The rest of the variables will be computed. The four equations are all interdependent on each other, and the tricky part is that the equation of col_h is quite complex. Appreciate your help, Thanks.

BY2 · ‎07-28-2020

Hi Bart, I have tested out the code and it works fine except for one thing: The output variables (sim_ML_final and sim_GL_final) increase as n increases. Can you explain the reason behind it?

BY2 · ‎07-28-2020

Hi, Sample data: ID colA colB colC colD colE1 colE2 colE3 colE4 colE5 colE6 colE7 colE8 colE9 ColW ColR Col_ip col_i99 col_IL col_h col_sr col_c col_ML 123 0.006544 0.5018 30758444 5 0.566207 -0.01396 0.245639 -0.09455 0.780985 0 0 0 0 0.000595 0.2065 -2.48137 3.090232 1748895 456 0.00265 0.231654 28265257 4 0.42042 -0.25934 0.423668 0.759272 0 0 0 0 0 0.000546 0.2251 -2.78821 3.090232 435886.1 789 0.006544 0.5018 20076895 8 0.174945 0.204222 0.217982 0.021944 -0.03473 0.212329 0.041425 0.911967 0 0.000388 0.2065 -2.48137 3.090232 1141552 1122 0.012851 0.501829 20062860 4 0.42042 -0.25934 0.423668 0.759272 0 0 0 0 0 0.000388 0.1831 -2.23069 3.090232 1585257 1455 0.035506 0.45 8535795 6 0.554116 0.341346 0.185772 -0.13075 0.144423 0.709912 0 0 0 0.000165 0.1403 -1.8054 3.090232 931034.2 1788 0.00265 0.45 6898495 8 0.174945 0.204222 0.217982 0.021944 -0.03473 0.212329 0.041425 0.911967 0 0.000133 0.2251 -2.78821 3.090232 206655.2 2121 0.029363 0.45 6614324 4 0.42042 -0.25934 0.423668 0.759272 0 0 0 0 0 0.000128 0.1476 -1.89024 3.090232 664473.7 2454 0.029363 0.45 5936919 6 0.554116 0.341346 0.185772 -0.13075 0.144423 0.709912 0 0 0 0.000115 0.1476 -1.89024 3.090232 596421.8 2787 0.029363 0.5018 5261641 5 0.566207 -0.01396 0.245639 -0.09455 0.780985 0 0 0 0 0.000102 0.1476 -1.89024 3.090232 589429.3 3120 0.012851 0.45 3664763 5 0.566207 -0.01396 0.245639 -0.09455 0.780985 0 0 0 0 7.09E-05 0.1831 -2.23069 3.090232 259662.9 3453 0.012851 0.45 2186744 4 0.42042 -0.25934 0.423668 0.759272 0 0 0 0 0 4.23E-05 0.1831 -2.23069 3.090232 154939.5 3786 0.05013 0.45 98330.52 8 0.174945 0.204222 0.217982 0.021944 -0.03473 0.212329 0.041425 0.911967 0 1.9E-06 0.1298 -1.64359 3.090232 12604.4 4119 0.001941 0.45 9.27E+08 3 0.589853 0.173527 0.788646 0 0 0 0 0 0 0.017929 0.2289 -2.88759 3.090232 22651290 4119 0.001336 0.45 17684656 3 0.589853 0.173527 0.788646 0 0 0 0 0 0 0.000342 0.2322 -3.00315 3.090232 334349.2 Would like to perform Excel Solver in SAS that solves col_h, col_sr, col_c and col_ML. These 4 variables equation are interrelated as shown below: 1. col_sr = sqrt(col_R/Y) 2. col_c = colB*colW*cdf('normal',((Col_ip+Col_R*Col_99)/sqrt(1-Col_R**2))) 3. col_ML = colB*colC*cdf('normal',((Col_ip+col_h*col_sr*Col_99)/sqrt(1-(col_h*col_sr)**2))) 4. col_h = sumproduct of (colE1-colE9, b1-b9) where b1-b9: cy1 = sumproduct(col_c*colE1); . . (repeat till cy9) . .cy9 = sumproduct(col_c*colE9); lm = sumproduct(cy1-cy9, cy1-cy9); b1 = cy1/lm . . (repeat till b9) . b9 = cy9/lm To solve Y, the difference of sum(col_ML) and sum(col_IL) is value of 0. **Note: SAS IML and Proc OptModel procedure is not found in my SAS License. Any help would be greatly appreciated. Thank you!

BY2 · ‎07-27-2020

An example of source1 will be something like this: ID, P,E,L,r,n,ho a1,0.5,10000,0.45,0.1,1,-0.3 a2,0.2,67795,0.55,0.6,2,0.55 a3,0.6,56781,0.66,-0.8,3,0.31 ID = Identity P = range from 0 to 1 E = greater than 0 L = range from 0 to 1 r = range from -1 to 1 ho = range from -5 to 5 n = row number You may generate the data sample based on the criteria above. My 'source1' dataset is around 4,000 observations. Hope this helps.

BY2 · ‎07-27-2020

1. By looking at the code, this will create 1 million of datasets, is that right? Is there any other method without create 1 million datasets and would speed up the process? 2. For this code particularly, do i need to add it to my data a since there is a rand() function? call streaminit(12345); /* to make it reproducible */ 3. I have replied to the response below which explains my ultimate goal of this simulation exercise. Kindly refer to the below. Appreciate your effort, Bart.

BY2 · ‎07-27-2020

I have considered this method but i do not want to overload the storage by creating a million datasets.

BY2 · ‎07-27-2020

Yes, I am trying to generate a random normal variate by using box muller transformation method. The ultimate goal of this simulation is to obtain the sum of two variables (sum_sim_ML & sum_sim_GL) with 1 million simulation. Let's use sum_sim_ML as the example. The equation of the both variables are similar as shown below. if mod(n,2)=0 then do; if r * ho * &&sim_1&i + sqrt(1-(r*ho)**2)*sim_m1 < P then sim_ML = E*L; else sim_ML = 0; end; else if mod(n,2)=1 then do; if r * ho * &&sim_1&i + sqrt(1-(r*ho)**2)*sim_m2 < P then sim_ML = E*L; else sim_ML = 0; end; /* where r, ho, E, L are from source1 table while sim_1, sim_m1 and sim_m2 are randon generating numbers (rng). Note: n is the total observation from source1 table. */ For each simulation (i=1 to 1,000,000), for example, when i=1, sim_1 is applied across all 4000 observations. However, sim_m1 and sim_m2 are RNG and should be different from every observations. After obtaining the parameters of the equation, each observation will have different sim_ML. Then, I use proc sql to get the summation of sim_ML. Finally, I compile all simulation of sum_sim_ML using proc append. I hope this explains well. Feel free to let me know if any further clarification is needed.

BY2 · ‎07-27-2020

Unfortunately I do not have license for SAS IML.

BY2 · ‎07-27-2020

Yes, n is the total number of rows in source1

BY2 · ‎07-27-2020

Thank you, will definitely try out this. Will keep you posted.

BY2 · ‎07-27-2020

source1 is the source data file. The size of source1 is not a huge data, around 4000 observations and 23 variables. The simulation that takes the most time is %macro mcarlo() and %sim_2() where it simulates 1 million random numbers.

Online Status	Offline
Date Last Visited	‎12-01-2020 11:31 PM

Re: Dynamic Variables

Dynamic Variables

Re: Excel Solver in SAS (By changing variable cells)

Re: Excel Solver in SAS (By changing variable cells)

Re: Excel Solver in SAS (By changing variable cells)

Re: To make my simulation code run faster (ideally less than an hour)

Excel Solver in SAS (By changing variable cells)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: Dynamic Variables

Dynamic Variables

Re: Excel Solver in SAS (By changing variable cells)

Re: Excel Solver in SAS (By changing variable cells)

Re: Excel Solver in SAS (By changing variable cells)

Re: To make my simulation code run faster (ideally less than an hour)

Excel Solver in SAS (By changing variable cells)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)

Re: To make my simulation code run faster (ideally less than an hour)