Hi --   Apologies if this isn't the best community section to post this in, I didn't see any communities on Enterprise Guide in particular.   In SAS Enterprise Guide 7.1 (on my Windows 7 machine) I am trying to open the 'Editor Options' (Tools->Options->SAS Programs->Editor Options...), and I get an "Application Error" from Enterprise Guide, and it won't allow me to access the Editor Options, which I want to do to add font colors, and add line numbers.   This is the error message: Error Message System Configuration   Does anyone have any ideas on what's going on and how I can fix this? Please let me know if I can provide any additional information. Thank you very much. ... View more

Hi --   Apologies if this isn't the best community section to post this in, I didn't see any communities on Enterprise Guide in particular.   In SAS Enterprise Guide 7.1 (on my Windows 7 machine) I am trying to open the 'Editor Options' (Tools->Options->SAS Programs->Editor Options...), and I get an "Application Error" from Enterprise Guide, and it won't allow me to access the Editor Options, which I want to do to add font colors, and add line numbers.   This is the error message: Error Message System Configuration   Does anyone have any ideas on what's going on and how I can fix this? Please let me know if I can provide any additional information. Thank you very much. ... View more

Hi All, I have a question about using proc autoreg with the "nlag" option specified for serial correlation correction. When there are significant AR terms included in the model from the "nlag" statement, there are two output parameter estimate tables, the first "Parameter Estimates" which includes the AR estimates, and then "Autoregressive parameters assumed given" table which does not include the AR terms -- I'm wondering which should be used for obtaining 1) the actual parameter estimates that one would want to use for forecasting of future values (for using the model in practice), and 2) which table has the correct p-values that should be referenced with regards to considering the real statistical significance of each variable to asses whether it should be retained in the model or not. I've been reading a bunch online, and have found some useful information and guidance, but I don't feel comfortable that I have a definitive answer here. I know that the "autoregressive parameters assumed given" table seems to match the parameter estimates output via the "outest=" option dataset, but I've read some material indicating that the "Full (conditional) model" is used for future predictions, which seems like it may suggest that I should be using the estimates from the first "Parameter Estimates" table inclusive of the AR times, but I may not be interperting this correctly (the material I am referencing is: http://support.sas.com/documentation/cdl/en/etsug/63348/HTML/default/viewer.htm#etsug_autoreg_sect003.htm If anyone has any information on this, or could at least point in the direction of some more straight-forward reference material, I would really appreciate it. Thank you!! ... View more

Hi All -- This may be an unusual task, and so I will try to explain the best I can please, please let me know if I don't explain the question well enough: I have a set of aggregated data, that i'd like to merge in such a way that it is duplicated for appropriate by-groups. I think the best way to illustrate what I want is with an example: This is data set of aggregate data (using dummy data here), essentially it is simple average balances across a number of months. There is a field indicating the number of months, the account, the average balance across that number of months: account average_bal num_months 1 50$ 1 1 55$ 2 1 54$ 3 2 130$ 1 2 135$ 2 2 133$ 3 So account is the account number, when num_months = 1, the average is really just the balance of the last month, when num_months = 2 its the average balance across the past two months, when num_months=3 then it's the average across last 3 months, etc. etc.. What I want is to have monthly data added to this, so that thee average across all months designated in "num_months" stays the same for each "num_months" group, but the monthly data is present, so this is what I'd like to have: account average_bal num_months month monthly_bal 1 50$ 1 august 50 1 55$ 2 august 50 1 55$ 2 july 48 1 54$ 3 august 50 1 54$ 3 july 48 1 54$ 3 june 55 2 130$ 1 august 130 2 135$ 2 august 130 2 135$ 2 july 140 2 133$ 3 august 130 2 133$ 3 july 140 2 133$ 3 june 137 Now I realize that the data doesn't actually match mathematically (the averages don't match the actual calculated average of the 'monthly_bal' values as they should in real life, as I just made up these numbers to illustrate the data structure I'm looking for). So assuming I have a dataset of monthly balances for each month and each account, i'd like to be able to merge and get the above table. A simple cartesian product doesn't get me exactly what I want, but close. I've tried many joining and merging methods with Proc SQL and Datasteps, but can't quite get it. Has anyone else had this problem, or know what I'm missing here? Thanks a lot! ... View more