I wanted to thank everyone for the responses. Sometimes when you are doing general searches on line you bring up an older system no longer being used. We don't have the tools to use even the old system I believe, and won't be able to purchase the newer system either (I am the only one in my unit who uses statistics, most do SQL). Time series models are becoming more important and perhaps this may change in the future. ... View more

Thank you so much. As I am very new to SAS... a few things are confusing for me right now. My first experience is on SAS Viya only. learning model studio for Hackathon. very happy for the resources shared by you. Thanks, Sir. ... View more

Hi, This was great...you identified the significance of synthetic data with relevance to statistical characteristics resemblance to real data & co relation maintained in the synthetic data 2 years back is a very thoughtful idea. I too really believe the growing importance of synthetic data in many other applications of clinical trials as significant impact in protocol design, patient enrollment strategy & others.  ... View more

@Jasmijn  You start with a well-chosen team name. That's promising. Ciao, Koen ... View more

@Serinac01 wrote: I used a simple decision tree and downloading that score code still resulted in astore procedure Yes , a simple decision tree also has its score code in an astore binary object.  As confirmed by the table on this page : SAS Help Center: Scoring Your Models Linear, logistic and quantile regression (a.o.) produce data step score code.   You can make your decision tree with PROC HPSPLIT. (the HP-prefix is for High-Performance , it's not a CAS-procedure but it works multi-threaded) PROC HPSPLIT  produces a file that contains SAS DATA step code for scoring new data produces a file that contains node rules You can integrate that PROC HPSPLIT in your Model Studio pipeline (SAS code node).   Ciao, Koen ... View more

Note that you can also use PROC MIXED and PROC GLIMMIX for fitting a model to panel data. Due to different (estimation) methods used , the results will not be identical to those from PROC PANEL. But PROC MIXED and PROC GLIMMIX do have an ESTIMATE statement.   See this (dated) article for a comparison between PROC PANEL and PROC MIXED. http://www2.sas.com/proceedings/forum2007/170-2007.pdf Usage Note 22114: Analyzing unbalanced panel data using PROC PANEL or PROC TSCSREG https://support.sas.com/kb/22/114.html (PROC MIXED is not the primary focus, but it is covered) Usage Note 22115: Estimating a model using the Parks method with unbalanced panel data https://support.sas.com/kb/22/115.html   The old TSCSREG procedure is also for panel data , but it does not have an ESTIMATE statement either.   Ciao, Koen ... View more

You are welcome.   You are comparing apples and oranges. If you want to compare the efficiency to the design you originally found (which does not conform to your desired restrictions) then you must evaluate the D-efficiency without the Block variable. This step will do that: %mktex(3 2 2 2 3 3 2 2, n=96, init=final(drop=block), options=check, interact=@2, seed=12345) When you impose restrictions, then you typically will get a lower D-efficiency. ... View more

@sasalex2024 wrote:   That said, I’d appreciate any thoughts on the UCM and CUSUM issues I mentioned above. Thanks again. This is how I would use the CUSUM method for Structural Break Detection / Change Point Detection in time series: Make an appropriate time-series model for your time series (it should fit the data well). Use PROC ARIMA or PROC SSM (for linear state space models) or PROC UCM or ... then proceed to Model-based Break detection methods that use CUSUM and/or CUSUMSQ statistics. CUSUM and CUSUMSQ statistics are computed using the cumulative sum and cumulative sum of squares of "one-step-ahead residuals" , respectively. With only a little bit of effort , you can use these residuals to do the CUSUM/CUSUMSQ-based change point detection as a post-fit diagnostic step. The CUSUM/CUSUMSQ-based change point diagnostics can be complementary to the De Jong-Penzer algorithm-based change point diagnostics. In particular, the CUSUM/CUSUMSQ-based change point diagnostics can be useful to detect changes in the variance of the process. Ciao, Koen ... View more

Hi, Rick   Thanks for the clarification. Now I see. Luckily, there is the DO Loop method. ... View more

You will need code similar to the following: filename mymail email from="Ron.Dave@gmail.com" TO=("Ron.Dave@gmail.com") subject="Update" type='text/html'; data _null_; file mymail; put '<html><body>'; put '<p>Hello</p>'; put '<p><font color="blue">Here is my report</font></p>'; put '</body></html>'; put '</html>'; run; ... View more

Take a look at 33307 - Scoring (computing predicted values) for new observations or a validation data set. Special thanks are given to @StatDave for introducing me this note. ... View more

Another customer was facing the same problem and referred to this topic in his query to me. In the end, it turned out it was not due to a (lack of) memory problem there ...but due to the fact that he had used an integer variable as a by-variable. That can't be done. The by-variables in the forecasting hierarchy should all be character variables (varchar e.g.).   Ciao, Koen ... View more

In PROC AUTOREG, in addition to ARCH/GARCH model specification, you can also use HETERO statement to specify error variance function:   https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/etsug/etsug_autoreg_syntax11.htm   And the HETERO statement can also be used with GARCH model together to specify additional variables in the variance function to the standard GARCH equation as discussed here:   https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/etsug/etsug_autoreg_details12.htm#etsug.autoreg.heterogarch     PROC MODEL allows more flexible specification of error variance structures as discussed here:   https://go.documentation.sas.com/doc/en/pgmsascdc/9.4_3.5/etsug/etsug_model_sect133.htm   If you have specific form of heteroscedasticity but not sure how to specify your model, please provide more details.   ... View more