About Rick_SAS

Rick_SAS · ‎10-10-2024

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" )?

Rick_SAS · ‎10-10-2024

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;

Rick_SAS · ‎10-10-2024

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?

Rick_SAS · ‎10-10-2024

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.

Rick_SAS · ‎10-10-2024

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.

Rick_SAS · ‎10-02-2024

There is no option to output the current amount of memory in use while the IML procedure is running. The method by which IML allocates and frees memory is complicated and is not documented.

Rick_SAS · ‎10-02-2024

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;

Rick_SAS · ‎10-01-2024

As I said, the doc is out of date and needs to be updated.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?

Rick_SAS · ‎10-01-2024

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.

Rick_SAS · ‎09-18-2024

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;

Rick_SAS · ‎09-18-2024

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.

Rick_SAS · ‎09-09-2024

Set LCL and UCL to a missing for the months prior to the cutoff date (01JAN2020). Or, assign LCL and UCL to the predicted value prior to the cutoff. The difference between these two choices determines whether the band region "flares out" at the cutoff date, or appears suddenly after the cutoff date. your choice. You didn't provide data, but here is an example: /* create fake data */ data Have; format Day Date10.; do Day = '01Jan2019'd to '01Mar2020'd by 7; pred = (Day-'01Jan2019'd)/50 + sin(Day/10); LCL = pred - 1; UCL = pred + 1; output; end; run; title "Sample Band Plot"; proc sgplot data=Have; band x=Day Lower=LCL upper=UCL; series x=Day y=Pred; run; %let cutoff = '01Jan2020'd; data Want; set Have; if Day < &cutoff then do; LCL = pred; /* or assign to missing value */ UCL = pred; end; run; title "Only Show Band On and After Cutoff"; proc sgplot data=Want; band x=Day Lower=LCL upper=UCL; series x=Day y=Pred; refline &cutoff / axis=x; run;

Rick_SAS · ‎09-05-2024

Can you say more about what you intend to do with these matrices? I have seen a few cases where the programmer thinks he needs to do. But in most cases, the program only requires one matrix at a time. If that i the case for your application, create the matrix, M, inside the loop, use it, and then use the same name for the next iteration. I've also seen applications where the program requires M_new and M_old. If that is the case, set M_old=M_new at the bottom of the DO loop, and reassign M_new at the top of the loop.

Rick_SAS · ‎08-22-2024

Yes, there are several ways to do this. Some researchers use the moment-ratio diagram to find a distribution that is close to the (skewness, kurtosis) value, then sample from that distribution. See The moment-ratio diagram - The DO Loop (sas.com) A chapter of the book Simulating Data with SAS shows how to implement this idea by using SAS 9.4. If you have SAS Viya, you can use PROC SIMSYSTEM, which enables you to specify the moments and will output the simulated samples. If you have actual data, I suggest you model the data by using the Johnson distribution, which is conceptually the easiest flexible system. You can use PROC UNIVARIATE to perform the fit. If your data are bounded (for example, tests scores that are between 0 and 100), use the Johnson SB distribution. See The Johnson SB distribution - The DO Loop (sas.com) If your data are unbounded, use the Johnson SU system. See The Johnson SU distribution - The DO Loop (sas.com) (There is also an algorithm for deciding between the SB and SU family; see The Johnson system: Which distribution should you choose to model data? - The DO Loop (sas.com)) After you have decided on a system and fit the parameters to the data, you can use the DATA step programs in those articles to produce random samples from the model.

Rick_SAS · ‎08-21-2024

1. Carefully read the articles. Pay attention to phrases like "if you are using a procedure that does not support the EFFECT statement..." 2. Use PROC GLMSELECT to output the design matrix for your model, which includes the spline effects 3. Use PROC SURVEYLOGISTIC to analyze the design matrix, which includes the spline effects. If you have additional question, please open a NEW thread and post the SURVEYLOGISTIC code that you want to produce, along with a description of which variable(s) should use spline effects.

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