turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

Topic Options

- RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

04-21-2014 03:27 PM

This question is related to a question I posted in the SAS/STAT forum ().

I have a large and sparse design matrix of ones and zeros (about 450k rows, 2500 columns). I'm trying to use this to run a regression, but SAS/STAT procedures are taking too long. (I ran proc hpmixed and it had not produced any results after 24 hours.)

If I read the data into Matlab as a sparse matrix, I can run a QR decomposition and invert the resulting matrix in less than 10 seconds. Is it possible to take this approach in IML? I feel like I must be missing something because it doesn't seem like this is a hard problem to solve, so I thought SAS would handle everything on the fly, but it seems that I'm going wrong somewhere.

Thanks for any advice.

- Mark as New
- Bookmark
- Subscribe
- RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Posted in reply to stoffprof

04-21-2014 04:56 PM

In your MATLAB example, if X = QR, then R and Q are dense 2500x2500 matrices, So I guess you are asking whether IML has a sparse QR decomposition? No, it does not.