Hi,
I have below fit with ordinal logistic regression
dat = foreign::read.dta("https://stats.idre.ucla.edu/stat/data/ologit.dta";)
summary(MASS::polr(formula = apply ~ pared + public + gpa, data = dat))
However, instead of obtaining unconstrained estimates of model
parameters, I would like to impose certain constraints on each of the
model parameters, based on some non-sample information.
Is there any R function to estimate model coefficients with imposing
some unser-defined constraints on the model parameters?
Any pointer will be very helpful.
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