Hi i am estimating a dummy panel regression to remove seasonality.
The equation goes something like this
Y = intercept + b mon + b2 tue + b3 wed + b4 thrsday + e
Now i want to calculate a variable which would be intercept+ e
i am using proc reg with a "by" variable
how to extract only the intercept and residual as a seperate data set.
I know how to extract residual , but extracting intercept is very tricky . By using outest command it gives me a very jumbled data set with alot of other observations too.
Is there any efficient way???
Thanks in advance for helping
It is quite straitforward to combine OUTEST= and OUT= datasets :
proc reg data=myData outest=myParms;
by myByVar;
model Y = mon tue wed thrsday;
output out=myRes r=resid;
run;
proc sql;
create table noSeason as
select R.myByVar, P.intercept + R.resid as Yp
from myParms as P inner join myRes as R on P.myByVar=R.myByVar
where P._TYPE_="PARMS";
quit;
PG
Thanks alot really appreciate
How is your date variable related to your other variables, especially to your BY variable(s)?
it is a panel data basically, for 500 stocks , daily data over 7 years. so my by variable is the stock name, which is to say o am estimating regression for every stock seperately,
i managed to get the desired result by manipulating the code you provided , kindly check if i have done it right or if there is a more efficient way kindly suggest that
proc sql;
create table noSeason1 as
select R.codneg, P.intercept + R.resid as Yp ,date
from myres as R inner join Myparms as P on R.codneg=P.codneg
where P._TYPE_="PARMS";
quit;
where codneg is the stock name variable, and rest is all the same as you suggested
That looks perfectly fine to me!
PG
Join us for SAS Innovate April 16-19 at the Aria in Las Vegas. Bring the team and save big with our group pricing for a limited time only.
Pre-conference courses and tutorials are filling up fast and are always a sellout. Register today to reserve your seat.
Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
Find more tutorials on the SAS Users YouTube channel.