[R] Estimating regression with constraints in model coefficients

[Christofer Bogaso]

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.