About oriti

oriti · ‎12-20-2016

Thank you!! you gave me few ideas and I used the expand procedure to fill missing values. In addition I added a spline function (msplint) to add more variables that I needed.

Rick_SAS · ‎09-26-2014

Being possible and being a good idea are two different things. Yes, it is possible. However, I agree with that evaluating (scoring) the model in SAS/IML will probably be simpler, since evaluating a model is just matrix multiplication. If you decide to go the SAS/STAT route, look into PROC SCORE. You would have to write the coefficients to a data set in the form that PROC SCORE could consume, as described here: SAS/STAT(R) 13.1 User's Guide

stat_sas · ‎09-18-2014

Thanks so much Dr. Rick. I was just mixing observations with cov matrix.

Rick_SAS · ‎07-14-2014

It sounds like you want a two-sided test. For a discussion, see How to compute p-values for a bootstrap distribution - The DO Loop . For a two-sided example (and code), see p. 14 of this paper: http://support.sas.com/resources/papers/proceedings10/329-2010.pdf

oriti · ‎05-07-2014

Thank you all! Well, the paper is from 2005 and the code (S-plus) just has been used in a paper from 2014. but, It's not a common procedure... Great community, thanks again, Orit

oriti · ‎04-25-2014

Brilliant !! Thanks so much, Orit

gin · ‎04-02-2014

Please check this works for you: x=(C^=0); Cnew=C[,loc(x[+,]^=0)];

oriti · ‎02-04-2014

Really interesting! Thank you Rick!

Rick_SAS · ‎01-21-2014

You didn't round, so the probability of a singular matrix is much lower. If you are good at math and numerical linear algebra, here is an article about generating random matrices and the probability of generating a singular matrix: What is the chance that a random matrix is singular? - The DO Loop

Rick_SAS · ‎12-19-2013

I'd allocate a row vector to hold the results and use a DO loop over the columns.

oriti · ‎10-29-2013

Rick, thank you!

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