# NOT RUN { # Fit the proportional odds model: pneumo <- transform(pneumo, let = log(exposure.time)) (fit1 <- vglm(cbind(normal, mild, severe) ~ sm.bs(let, 3), cumulative(parallel = TRUE, reverse = TRUE), data = pneumo)) coef(fit1, matrix = TRUE) constraints(fit1) # Parallel assumption results in this constraints(fit1, type = "term") # Same as the default ("vlm"-type) is.parallel(fit1) # An equivalent model to fit1 (needs the type "term" constraints): clist.term <- constraints(fit1, type = "term") # "term"-type constraints (fit2 <- vglm(cbind(normal, mild, severe) ~ sm.bs(let, 3), data = pneumo, cumulative(reverse = TRUE), constraints = clist.term)) abs(max(coef(fit1, matrix = TRUE) - coef(fit2, matrix = TRUE))) # Should be zero # Fit a rank-1 stereotype (RR-multinomial logit) model: fit <- rrvglm(Country ~ Width + Height + HP, multinomial, data = car.all) constraints(fit) # All except the first are the estimated A matrix # }
Run the code above in your browser using DataCamp Workspace