sas >> IMLPlus and IML Workshop

by Harold.Nelson » Wed, 12 Mar 2008 05:15:32 GMT

Does anyone know what happens to IMLPlus and IML Workshop with SAS 9.2?
Will version 2.1 still work? =20
=20
Harold L. Nelson, Jr. PhD
Sr. Forecast Coordinator
OFM Forecasting
Voice: (360)902-0603=20
=20

sas >> IMLPlus and IML Workshop

by mehdi_soleymani » Wed, 12 Mar 2008 19:06:14 GMT


On Tue, 11 Mar 2008 14:15:32 -0700, Nelson, Harold (OFM)


I think SAS stat studio use IMLPlus.

Similar Threads

1. SAS/IML Workshop 2.1

2. Listing combinations in IML (was Reducing a matrix in IML iteratively)

>
> Date:    Wed, 29 Dec 2004 12:51:05 -0800
> From:    Dale McLerran < XXXX@XXXXX.COM >
> Subject: Re: Reducing a matrix in IML iteratively
>
> --- "Tonidandel, Scott" < XXXX@XXXXX.COM > wrote:
>
> > Dale,
> >
> > Thanks for the helpful suggestions. I think the macro is the way to
> > go
> > because this code is part of a larger simulation study that may have
> > as
> > many as 8 X-variables. I think I am going to go with the second macro
> > you suggested below but this led to a few additional questions (I
> > hope
> > you don't mind this additional imposition -- if so my apologies). The
> > first question has to do with the scope of my problem while the other
> > two stem more from my unfamiliarity with combining macros and IML.
> >
> > 1) I was originally thinking about reducing the entire correlation
> > matrix and then pulling the parts out of that reduced matrix that I
> > need (Sxx, Syy, Sxy). But, I liked the idea you presented to focus
> > on a piece of the original correlation matrix (Sxx in this case)
> > and reduce that.  But this leaves the additional step of me having
> > to reduce the Syy, and Sxy matrices as well. Is there an easy way
> > you would recommend doing that in the context of your macro?
>
> The Sxy matrix can be subset using the index vector.  Just
> employ Sxy[index,] and also Syx[,index].  I was under the
> impression that all Y variables would be included in the
> multivariate R-square computation, so that no subscripting would
> be needed for Syy.  If that is incorrect, then you will need
> additional loops which form an index for the columns of the
> multivariate response.
>
> >
> > 2) As I said earlier this is actually a piece of a larger simulation
> > where I am generating data with various numbers of predictor
> > variables and criterion variables so this will be nested within a
> > larger do loop.  In my larger program I have a scalar variable
> > called numpred which is indexed from 2 to 8 so the &columns
> > variable in your macro will need to take on these values. But,
> > the macro will not let me put numpred as an argument b/c it treats
> > it as text. I am not very familiar with combining macros and IML so
> > how would I make this numpred variable an argument in the macro?
>
> If I understand correctly, you have code something like the
> following:
>
>   do numpred=1 to 8;
>     do iter=1 to 1000;
>       <generate X data with numpred columns>
>       <generate Y data with numcrit columns>
>       <obtain multivariate R-square of Y with every combination of X>
>     end;
>   end;
>
>
> Now, employing the code that I posted yesterday, you would need
> to have NUMPRED inner do loops in order to obtain the multivariate
> R-square for every possible combination of the columns of X.
> But the number of loops cannot depend on the IML variable NUMPRED.
> Thus, the code that I sent yesterday will not work.
>
> Here is a different solution which will work for the problem
> described above.  We know that there are ((2**NUMPRED)-1)
> combinations of the predictor variables that must be considered.
> Now, if we loop from 1 to ((2**NUMPRED)-1) and convert the loop
> index value to binary, then we will have a set of values that
> are constructed as
>
>    do loop                      reversed
>     value     binary value    binary value
>       1         00000001        10000000
>       2         00000010        01000000
>       3         00000011        11000000
>       4         00000100        00100000
>      ...           ...             ...
>
>
> Note that I have represented the binary variable with eight digits
> which is the maximum value for the index variable NUMPRED.  Now,
> we can treat the columns of the reversed binary value as indicators
> for the columns of X that we should select for the indexed
> combination.  Below is code which constructs the reversed binary
> value, and from that constructs an index for the columns of X
> that should be selected.
>
>     proc iml;
>       do numpred=1 to 4;
>         do i=1 to ((2**numpred)-1);
>           Xcols = reverse(putn(i,"binary8."));
>           do j=1 to numpred;
>             xj=num(substr(Xcols,j,1));
>             if j=1 then index=xj*j;
>             else index=index || xj*j;
>           end;
>           index = loc(index);
>           print numpred Xcols index;
>         end;
>       end;
>     quit;
>
<stuff removed>

> HTH,
>
> Dale
>
> =====
> ---------------------------------------
> Dale McLerran
> Fred Hutchinson Cancer Research Center
> mailto:  XXXX@XXXXX.COM 
> Ph:  (206) 667-2926
> Fax: (206) 667-5977
> ---------------------------------------

Dale,

I like the trick of looping over all possible combinations using
the binary numbers, however this does bring with it some overheads,
specifically the character string manipulation and then building up
the matrix index by repeated concatenation with itself.  Below
is some IML code for enumerating combinations that I have
taken from an old program that calculates multiple-case influence
diagnostics.  For me this has several advantages, firstly that
the subsets of different size are kept separate and secondly
that it should be a lot more efficient when the number of
combinations rises into the thousands.

proc iml;
  reset noname;
  /* IML module to loop over all combinations of k things from n.
     Subsets are enumerated in increasing subset size from k1 to k2.
  */
  start comblist(n,k1,k2);
    do k=k1 to k2;
      ncomb=round(exp(lgamma(n+1)-lgamma(k+1)-lgamma(n-k+1)));
      index=1:k;
      index[k]=k-1;
      last=(n-k+1):n;
      do s=1 to ncomb;
        j=k;
        do while (index[j]=last[j]);
          j=j-1;
        end;
        index[j]=index[j]+1;
        do i=j+1 to k;
          index[i]=index[i-1]+1;
        end;
        print index [format=3.0];
      end;
 end;
  finish;
  run comblist(8,1,8);
quit;
run;

Kind regards,

Ian.

Ian Wakeling
Qi Statistics.

3. UNR Extended Studies presents 3-day Hands-On workshops in Reno NV

4. SAS workshops

Does anybody know of a SAS workshop or course online or anywhere in
North America? I live in Vancouver, what I wouldn't mind flying
somewhere else for a good workshop.

I use SAS for my data analysis. However, when I try a new procedure, I
usully feel I do not find enough information online and in books to
interpret the outputs and to know how to use the different available
options when writing the code.
I do not need an introductory course to the system. I have already
taken a couple of those. I think I am already a step further.... I
feel kind of stuck in my learning procedure, and very unconfident when
I learn on my own (which it is what I usually do, I reckon as
everybody else does).

Thanks!

5. CFP: SIAM (SDM-05) Workshop on Feature Selection for Data Mining - Interfacing Machine Learning and Statistics

6. Call for papers - Workshop on Scheduling and Resource Management

                             Call for Papers
       Workshop on Scheduling and Resource Management for Parallel and
                       Distributed Systems (SRMPDS '05)
       To be held in conjunction with Intl Conference on Parallel and
       Distributed Processing Techniques and Applications (PDPTA '05)
               Las Vegas, Nevada, USA, June 27 - 30, 2005

SCOPE:
The goal of this workshop is to bring together researchers and
practitioners working in the areas of resource scheduling and resource
management to exchange and share their experiences, new ideas, and
latest
research results on all aspects of scheduling and resource management
in
parallel and distributed systems.

TOPICS OF INTEREST:
Topics of interest for the workshop include, but are not limited to:
Resource allocation and management
Advance resource reservation and scheduling
Load sharing and Load balancing techniques
Network resource allocation
Fault-tolerant resource management approaches
Data access and management
Scheduling on heterogeneous nodes
Time slicing, gang, or co-scheduling
Fairness, priorities, and accounting Issues
Performance implications of scheduling strategies
Performance metrics to compare scheduling schemes

PROCEEDINGS:
The proceedings of this workshop will be published together with the
proceedings of other PDPTA '05 workshops by the CSREA Press.

PAPER SUBMISSIONS:
Authors are requested to submit papers (in PDF format) not exceeding 7
single-spaced pages, including abstract, five key words, contact
address,
figures, and references. E-mail your manuscripts to:  XXXX@XXXXX.COM 

IMPORTANT DATES:
Submissions Due:      Mar 14th, 2005
Review Decisions:     Apr 8th, 2005
Final Manuscript Due: Apr 20th, 2005

PROGRAM CHAIR:
Rajkumar Kettimuthu (Argonne National Laboratory, USA)

PROGRAM COMMITTEE:
Suhui Chiang (Portland State University, USA)
Tae-Young Choe (Kumoh National Institute of Technology, Korea)
Zongfen Han (Huazhong University of Science and Technology, China)
David Jackson (Cluster Resources Inc, USA)
Barry Lawson (University of Richmond, USA)
Chanik Park (Pohang University of Science and Technology, Korea)
Anandha Srinivasan (IBM, India)
Achim Streit (Research Center Julich, Germany)
Ramin Yahyapour (University of Dortmund, Germany)

ADDITIONAL INFORMATION:
www.mcs.anl.gov/~kettimut/srmpds or send email to  XXXX@XXXXX.COM 

7. 1st CFP: International Workshop on Feature Selection for Data Mining

8. Call For Papers: Workshop on Scheduling and Resource Management

A remainder ...

Extended Paper Submission Deadline: March 14, 2005
==================================================
                             Call for Papers
       Workshop on Scheduling and Resource Management for Parallel and
                       Distributed Systems (SRMPDS '05)
       To be held in conjunction with Intl Conference on Parallel and
       Distributed Processing Techniques and Applications (PDPTA '05)
               Las Vegas, Nevada, USA, June 27 - 30, 2005

SCOPE:
The goal of this workshop is to bring together researchers and
practitioners working in the areas of resource scheduling and resource
management to exchange and share their experiences, new ideas, and
latest
research results on all aspects of scheduling and resource management
in
parallel and distributed systems.

TOPICS OF INTEREST:
Topics of interest for the workshop include, but are not limited to:
Resource allocation and management
Advance resource reservation and scheduling
Load sharing and Load balancing techniques
Network resource allocation
Fault-tolerant resource management approaches
Data access and management
Scheduling on heterogeneous nodes
Time slicing, gang, or co-scheduling
Fairness, priorities, and accounting Issues
Performance implications of scheduling strategies
Performance metrics to compare scheduling schemes

PROCEEDINGS:
The proceedings of this workshop will be published together with the
proceedings of other PDPTA '05 workshops by the CSREA Press.

PAPER SUBMISSIONS:
Authors are requested to submit papers (in PDF format) not exceeding 7
single-spaced pages, including abstract, five key words, contact
address,
figures, and references. E-mail your manuscripts to:  XXXX@XXXXX.COM 

IMPORTANT DATES:
Submissions Due:      Mar 14th, 2005
Review Decisions:     Apr 8th, 2005
Final Manuscript Due: Apr 20th, 2005

PROGRAM CHAIR:
Rajkumar Kettimuthu (Argonne National Laboratory, USA)

PROGRAM COMMITTEE:
Suhui Chiang (Portland State University, USA)
Tae-Young Choe (Kumoh National Institute of Technology, Korea)
Zongfen Han (Huazhong University of Science and Technology, China)
David Jackson (Cluster Resources Inc, USA)
Barry Lawson (University of Richmond, USA)
Chanik Park (Pohang University of Science and Technology, Korea)
Anandha Srinivasan (IBM, India)
Achim Streit (Research Center Julich, Germany)
Ramin Yahyapour (University of Dortmund, Germany)

ADDITIONAL INFORMATION:
www.mcs.anl.gov/~kettimut/srmpds or send email to  XXXX@XXXXX.COM