It might be insightful to find out how large the data can be before the problem occurs. For example, instead of  READ ALL VAR ... you could try  %let size = 1000; use work.olsmat; read next &size var {g1 g2 g3 g4 g5 g2_g1 g4_g1 g3_g1 g5_g1}; close; etc %let nobs = 1000; read next &size  ... View more

Ah! Thanks, I was confused. In that case, I don't know why you are getting an out-of-memory error. ... View more

Are you running the program on a Windows machine? Based on your description, I am going to guess that the issue is that your data are so big (16591 obs) that the Jacobian matrix exceeds 2GB. In fact, as discussed in the article, How much RAM do I need to store that matrix? - The DO Loop (sas.com) the jacobian matrix for your problem occupies 2.05 GB. Some of the legacy computational routines have 2GB allocation limits, and I know that NLPQN first appeared in SAS version 6, so it classifies as a "legacy" procedure.   I suspect if you read less than 16,000 observations, the routine will not complain about out of memory. Of course, it could encounter other issues.   ... View more

Instead of trying to attach it, can you paste it into the SAS Code Window by clicking the "Insert SAS Code" icon (aka, the "running man icon" )? ... View more

I think the jacobian of the NLC is wrong. In the CONSTR function you define matc[7,1] = prov*g3_g1; matc[8,1] = prov*g4_g1; but in the JACOBIAN function you define jac7 = g4_g1`/prov; /* jac7 and jac8 need to be switched */ jac8 = g3_g1`/prov; ... View more

1. Can you post the SAS log that you get when you run the program? 2. You said, "The choice variable is a vector with 16,000+ nonnegative entries." Does that mean WORK.PARAM and WORK.OLSMAT datasets have 16,000+ values? If not, what is the number of rows for those datasets? ... View more

From the program, it looks like you have 9 inequality constraints in the CONSTR function. But you have specified only three constraints in the option vector: optn[10]=3; /* number of nonlinear constraints */ I suggest you try using 9 instead. If I'm misunderstanding, then please explain more about the problem you are trying to solve. ... View more

You seem to be asking about how to write a macro loop that iterates over (i,j) pairs where i <= j.  Look at this example. Hope it helps.     %let n = 4; %macro TRI; %do i = 1 %to &n.; %do j = &i. %to &n.; %put &=i, &=j; %end; %end; %mend; %TRI; The key is to start to J loop at &i instead of at 1.   ... View more

You can use the SHOW NAMES statement (or SHOW ALLNAMES) to see which symbols have been defined. You can add the MODULES option if you want to see the names of the user-defined modules.   proc iml; N = 10000; print "--- 1 ---"; x = j(N, N); /* allocate matrices and vectors */ z = 1:N; w = z`; show names; start foo(x); return 1; finish; Q = x; print "--- 2 ---"; free x; /* free memory for x */ show names modules; print "--- 4 ---"; free / z w; /* free all symbols except for z and w */ show names; ... View more

As I said, the doc is out of date and needs to be updated.   What are you trying to accomplish? What information do you need about memory usage, and what do you intend to do with it? ... View more

Thank you for pointing to the documentation. The code you are running in SAS ODA uses a different system of memory management than is discussed in the documentation. What you are reading is out of date and needs to be updated. SAS IML no longer uses garbage collection, nor does it use "symbol space" and "workspace" the way it used to. Consequently, the output from the SHOW MEMORY statement is not useful or relevant.   ... View more

Yes. Assuming the method of moments converges, PROC UNIVARIATE will create the ParameterEstimates table. You can write any SAS table to a data set by using the ODS OUTPUT statement. See ODS OUTPUT: Store any statistic created by any SAS procedure - The DO Loop   /* Johnson SB(threshold=theta, scale=sigma, shape=gamma, shape=delta) */ data SB(keep= X); call streaminit(1); do i = 1 to 1000; x = rand("Lognormal", 0, 0.4); output; end; run; /* set bins: https://blogs.sas.com/content/iml/2014/08/25/bins-for-histograms.html */ proc univariate data=SB; histogram X / SB(theta=0 sigma=145 fitmethod=moments); ods output ParameterEstimates = PE; output out = temp_file_1 mean = x_var_Mean std = x_var_Std; run; data _null_; set temp_file_1; call symput('x_var_Mean', x_var_Mean); call symput('x_var_Std', x_var_Std); run; data _null_; set PE; if symbol='Delta' then call symput('dist_delta', Estimate); if symbol='Gamma' then call symput('dist_gamma', Estimate); run; %put &=x_var_Mean; %put &=x_var_Std; %put &=dist_delta; %put &=dist_gamma; ... View more

once you have the location, scale, and shape parameters of the distribution from using proc univariate, is there a way to assign them to a variable name in the same way we can do it with SAS summary statistics (e.g., max = name_for_max)? Or do I have to assign the value manually in the code (e.g., theta = 1.12345)? What "code" are you referring to? Show us your syntax. The doc for the HISTOGRAM statement in PROC UNIVARIATE specifies that the syntax for the options to the parametric density keywords are of the form THETA=value-list SIGMA=value-list so the option requires specifying a list of values, not a variable name.   You could use CALL SYMPUTX in a DATA _NULL_ step to assign values in a data set to macro variables. But that trick doesn't work if you are using BY-group proccessing.   ... View more