Hello!
I need to use one model used in previous papers but, of course, do not know the code for that,
It is the regression of credit ratings on some indicator variables(like loss or income) and others(like sales).
As there are more than 20 different credit rating scores and I need to use some indicator variables, I am lost how to make the code.
I find many about using categorical predictors but unsure about categorial regressees. Maybe using Logit/Probit thing...
e.g. : Credit Rating = b0+b1Sales+b2Loss indicator+b3dividend indicator...
If you already have worked on credit rating regression like this, please share your wisdome!
Thank you!!!
Jerry
I would use Partial Least Squares regression instead of ordinary least squares regression, and your indicator variables go into the CLASS statement, all variables go into the MODEL statement.
Documentation with examples:
Logit and probit are only used when the Y-variable is categorical; it is not used when an X-variable is categorical and the Y-variable is continuous.
I would use Partial Least Squares regression instead of ordinary least squares regression, and your indicator variables go into the CLASS statement, all variables go into the MODEL statement.
Documentation with examples:
Logit and probit are only used when the Y-variable is categorical; it is not used when an X-variable is categorical and the Y-variable is continuous.
Control variables ought to be included in the model the same as any other variables.
There is no ABSORB statement in PROC PLS.
If you really have a class variable that needs an ABSORB statement in PROC GLM, you'd have to include it in the model as a class variable in PROC PLS.
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