Yes, I know that my code doesn't have this problem, but my code DOES have the same form as your code: the WHERE condition is changing in a loop. I can't reproduce your problem, so I was hoping that you might be able to get it to happen with a data set that we both have access to. ... View more

I've never seen this warning before, but you say that "the values of thislot and thiswfr change during the loop" which makes me think that is the cause. Can you make it happen with SASHELP.class by modifying the following code? proc iml; gender = {F M}; cutoff = {60 62}; do j = 1 to ncol(gender); s = gender ; c = cutoff ; use sashelp.class where(sex=s & height read all var {Height} into h; print h; end; close sashelp.class; ... View more

Yes, this can be tricky. I need to write a blog post about this (http://blogs.sas.com/iml), since several people have asked a similar question. The issue, for those not familiar with calling Base SAS functions, is that some Base SAS functions string out their arguments in a list, whereas in SAS/IML it is convenient to be able to pass a vector of values. The trick is to convert the vector of values into a comma-delimted string, and then stick the string into a macro variable by using the SYMPUT function. (This technique appears in my book Statistical Programming with SAS/IML Software: http://support.sas.com/publishing/authors/wicklin.html) The following statements define a SAS/IML module called GetArgList that taks a vector of values and creates a comma-delimited string from it. You can then stick that string into the macro &myArgs, and use it in the FINANCE function: proc iml; start GetArgList(v); /* convert numeric elements to a single string */ y = strip(putn(rowvec(v),"BEST12.")) + ","; /* get rid of last comma */ y[ncol(y)] = strip(putn(v[ncol(y)],"BEST12.")); return( rowcat(y) ); /* scalar string */ finish; use test; read all var _ALL_ into values; call symput("myArgs", GetArgList(values)); r = finance('xirr', &myArgs, 0.1); print r; ... View more

I assume you've already read the documentation: http://support.sas.com/documentation/cdl/en/imlug/63541/HTML/default/viewer.htm#imlug_langref_sect207.htm This includes references to paper, articles, and books. For a general understanding of numerical optimization, read Fletcher, R. (1987), Practical Methods of Optimization, Second Edition, Chichester, UK: John Wiley & Sons. or Gill, E. P., Murray, W., and Wright, M. H. (1981), Practical Optimization, New York: Academic Press. ... View more

Sure. In that case you'll have to know (somehow) the size of the matrix in which you want to store the data. Let's say that you know numRow and numCol. I haven't tested (or even run) the following statements, so forgive any typos. If you are using SAS/IML 9.22, you can use the FULL function: http://support.sas.com/documentation/cdl/en/imlug/63541/HTML/default/viewer.htm#imlug_langref_sect098.htm read all var {element row col} into s; A = full(s); If you aren't using SAS/IML 9.22, then allocate A and then fill the nonzero elements by using the sub2ind module that I wrote about on my IML blog a few months ago: http://blogs.sas.com/iml/index.php?/archives/86-Converting-Matrix-Subscripts-to-Indices.html read all var {element row col}; A = j(numRow, numCol, 0); idx = sub2ind(numCol, row||col); A[ idx ] = element; (You *are* reading my blog, right? 🙂 ) ... View more

If you know the dimensions of the matrix ahead of time (3 x 3 for your example), you can just say: use MyData; read all var {element}; A = shape(element, 3, 3); If the number of rows and columns are unknown, then: read all var {row col element}; A = shape(element, max(row), max(col)); ... View more

This question isn't related to SAS/IML, so I think it would be better to ask follow-ups in a different forum such as http://support.sas.com/forums/forum.jspa?forumID=6 That said, here are two references you might find useful: http://www.nesug.org/proceedings/nesug04/io/io09.pdf http://www.lexjansen.com/pharmasug/2006/posters/po13.pdf ... View more

I'll remind everyone that this text editor treats LeftBracket-i-RightBracket as "begin italicize." To work around this, use a different index variable (such as x ) or put a space between the brackets (such as x[ i ]). ... View more

You can use the RANDGEN call, which includes optional arguments for the mean and Std Dev. You first need to allocate a vector to store the data: proc iml; n=10; E = j(n,1); do i = 1 to 50; call randgen(E, "Normal", 0, 4); end; You can also get all 50 variables at once. Each column of the following matrix contains a sample from N(0, 4). E = j(n,50); call randgen(E, "Normal", 0, 4); For comments on generating random vectors efficiently, see http://blogs.sas.com/iml/index.php?/archives/9-Efficient-Sampling.html For a description of how to generate 50 variables that each have a different distribution, see http://blogs.sas.com/iml/index.php?/archives/117-How-to-Sample-from-Independent-Normal-Distributions.html ... View more

No. You want cov = corr # (t(sigma) * sigma); which is a matrix, whereas sigma * t(sigma) is a scalar. This is Method #3 in the following blog post, which describes how to convert between correlation and covariance matrices: http://blogs.sas.com/iml/index.php?/archives/49-Converting-Between-Correlation-and-Covariance-Matrices.html ... View more

You didn't give the error message, so I don't know which of the errors you might be referring to. I see a few: (1) SAS/IML indexes vectors from 1, so the expression optn=j(0,11,.) is incorrect. (2) IML uses local variables in modules, so the variables estvar,col1,col2,col3, etc, are undefined within the modules. Maybe you intended to use a GLOBAL clause? ... View more

Sounds like an interesting problem. Could you post a simple example (4 or 5 observations) and the code you have so far, so we can better understand the problem? I've never used PROC ASSIGN so it would be helpful to see an example. ... View more

Is there a way? Yes, but that doesn't mean it is the best or easiest way. If you previously used PROC ASSIGN (which is part of SAS/OR software), I suggest using PROC OPTMODEL, which provides a natural way to specify linear programming problems and is designed specifically for linear programming. For details and an example, see http://support.sas.com/kb/42/143.html ... View more

That was recently discussed on the following thread: http://support.sas.com/forums/thread.jspa?threadID=12881&tstart=0 ... View more