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sorry...here's the full code: data prices; input date mmddyy10. price: 8.2 volume: 8. price2: 8.2 volume2: 8.; cards; 03/25/2005 15.78 1000 1.88 1500 09/05/2006 10.88 2000 0.77 2500 ; run; data prices(drop=price2 volume2); set prices(keep=date price volume) prices(in=b keep=date...

I'm no wiz with compound input statements, but the following will work: data prices(drop=price2 volume2); set prices(keep=date price volume) prices(in=b keep=date price2 volume2); if b then do; price = price2; volume = volume2; end; run;

Have you looked into proc arima...I know you can fit GARCH models with arima.

%let Varlist=c1,f,g,r..etc I do have some fixed variables, I would make them as macro variables. will that work? here are my code, correct me if i am wrong. I need some explanation too. %macro logisitic(); %let Varlist = c1 c2 c3 ... c100; /*all of my 100 predictors aren't of the order c1, c2...

proc logistic doesn't have an option to cycle through variable names...but you can use a macro, all you need is a macro variable with all the var names you want to test (Varlist): %macro logisitic(); %let Varlist = c1 c2 c3 ... c100; %let i = 1; %let CurrVar = %scan(&Varlist., &i.); %do %until...

your code looks correct, sounds like you don't have a license for SAS/STAT...to find out, type in proc setinit; run; and look for SAS/STAT in the list of SAS products your company is licnesed to use.

Use a chi-square test... proc freq data=yourdata; tables var1 * var2 / chisq; run; generally a p-value < 0.05 means there is a statistically significant difference in the category frequencies of the variables being tested.

hi kdt82, just tried it one day years ago and it worked

kdt82, FYI - the code i posted works perfectly in SAS. there is no do/end required for daisy chaining if then if then statements like that.

check the actual length of region1, if it is 7 or less then you will get an error. try using a condition to check the length before the conditional statement RegLen = length(Region1); if reglen > 7 then if substr(Region1,RegLen-7,8) = "Division" then Region2 = cat(Region1," Support");

any book on generalized linear models for sas would do. why are you using the gamma distribution, are you modeling a sum of normal random variates?

what link function are you using? can you post a sample of the output?

Here's one thing you can try....specify a larger standard deviation and discard the outliers. The shaprio-wilkes test for normality has a very high p-value (>.95) indicating perfect normality: data sim; do i=1 to 1000; x = rand('NORMAL', 25500, 10000); if 1000 <= x <= 50000 then output; end...

i would specify a mean of 25,500 (50000/2 + 1000/2) and a standard deviation big enough to spread the random variates from 1000 to 50000. An SD aroud 8000 will get you in the ballpark, but to my knowledge there's no way to restrict random variates in SAS to a specified range. You can discard the...

Use the rand function: x = RAND('NORMAL',Mean, Standard deviation)

data have2; set have; retain userid2; if userid ne '' then userid2 = userid; run;

the namelen = 32 option in the proc statement does the trick.

I'm using ODS to output parameter estimates from proc logistic to an output data set. ODS is truncating my variable names to 20 characters. Anyone know a work-around for this? proc template perhaps? data x; DO I=1 TO 1000; THIS_VAR_IS_EXACTLY_28_CHARS = RANUNI(1); DEPVAR = (RANUNI(2) < .25)...

ok, do you want to run your sas programs in batch mode or interactve...i'm not sure what distinction you are making regarding the enhanced editor, do you want to be able to see you log, output, run programs, code segments in the same editor? if you are talking about interactive mode under unix...

chris - just out of curiousity why do you think tagsort doesn't work well?