Hi everybody,   I have a dataset with a column of dates that looks like this:   Date 19940912 20031130 20130228 19960531 19990503   When I see the column attributes, the format is YYDDMMN8. and the informat 8.   I'm in the process of merging this dataset with another by date, and in the other dataset, the date has format and informat best12. and best32., respectively. The merging won't work, and I'm assuming it's because the date formats are different. How can I change the format and informat to match each other?   I googled and tried the following: data want; set have;     date_new=input(put(date,8.),best12.);     attrib  date_new informat=best32.; run;   and date_new looks like this:   date_new 12571 12906 16834 19590     Please help. How can I properly change the format and informat to best12. and best32.? Thanks a lot! ... View more

Hi all, I'm having some difficulties with the retain statement and hope to get help from y'all. I have a data set that contains unique ID and years, as well as a return variable. Basically it looks like this: ID     Year     Return 1     2010     1.03 1     2011     0.98 1     2012     1.05 2     2009     1.06 2     2010     0.89 3     2011     1.12 3     2012     1.01 3     2013     1.10 .     .               . .     .               . .     .               . What I want to get is to compute for each ID, the products of all the returns. For example, for ID 1: 1.03 * 0.98 * 1.05; for ID 2: 1.06 * 0.89; and for ID 3: 1.12*1.01*1.10. The following is my code: data want; set have;     by id;     retain product 1;     final = product * return;     if last.id then output; run; The results I got is simply the last return data for each ID, instead of the products. It seems that SAS isn't doing iterations for me, so there must be something wrong with my code. Any ideas? Any help is much appreciated! Thank you. Jolynn ... View more

Hi, everyone. I need to do a median regression and I believe I should use the procedure iml, which I know nothing about. Below is a sample code I had found online at http://www.ats.ucla.edu/stat/sas/webbooks/reg/chapter4/sasreg4.htm and I need your help in understanding what they are. My comments are in blue color. proc iml ; /*Least absolute values*/   use elemapi2;                                I think elemapi2 is the dataset   read all;   a = cons || acs_k3 || acs_46 || full || enroll;                 so a is the independent variables set. cons is the constant, acs_k3, .... and enroll are all independent variables.   b=api00;                                                                   api00 is the dependent variable   opt= { . 3 0 1 };                                                          opt seems to mean output, but I have no idea what { . 3 0 1 } is. HELP!   call lav(rc,xr,a,b,,opt); /*print out the estimates*/                what is rc and xr? Does opt mean to print out the estimates?     opt= { . 0 . 1 };                                                                opt again. { . 0 . 1 } seems to mean something different from { . 3 0 1 } . What is it? call lav(rc,xr,a,b,,opt); /*no print out but to create the xr*/ pred = a*t(xr);                                                        Calculate the predicted variable   resid = b - pred;                                                        calculate the residual   create _temp_ var { api00 cons acs_k3 acs_46 full enroll pred resid};                  create a dataset _temp_ to contain all variables, the predicted, and the residual   append;                                                          This seems to have something to do with the dataset just created quit; After this is run, the result is something like this. L1 Solution with ASE Est 17.1505029 1.2690656888 7.2240793844 5.3238408715 -0.124573396                           So the Est. here is the coefficients? ASE 123.531545 6.3559394265 2.2262729207 0.602359504 0.0391932684                           And these are the standard errors? I know these are really dumb questions. But I'm learning from zero. Thanks ahead for your help! ... View more

Hi everyone! I have a dataset with a column 1 of stock return numbers, with each row representing a company. Now I'm supposed to calculate a new column 2, being the empirical cumulative distribution function (CDF) of column 1. I don't necessarily need the function itself, I just need to get the density number for each company. So basically, all the numbers in column 1 is supposed to follow this CDF, and each company has a different density number, based on its column 1 return. I hope I've made myself clear... I googled about it and found a "severity" procedure. Maybe my SAS system is too old but it says " Procedure SEVERITY not found." I wonder if there's a simple solution to my problem. Many thanks! ... View more