1 개요
- R polr()
- "Ordered Logistic Or Probit Regression"
<source lang='r' run> options(contrasts = c("contr.treatment", "contr.poly")) house.plr <- polr(Sat ~ Infl + Type + Cont, weights = Freq, data = housing) house.plr summary(house.plr, digits = 3)
- slightly worse fit from
summary(update(house.plr, method = "probit", Hess = TRUE), digits = 3)
- although it is not really appropriate, can fit
summary(update(house.plr, method = "loglog", Hess = TRUE), digits = 3) summary(update(house.plr, method = "cloglog", Hess = TRUE), digits = 3)
predict(house.plr, housing, type = "p") addterm(house.plr, ~.^2, test = "Chisq") house.plr2 <- stepAIC(house.plr, ~.^2) house.plr2$anova anova(house.plr, house.plr2)
house.plr <- update(house.plr, Hess=TRUE) pr <- profile(house.plr) confint(pr) plot(pr) pairs(pr) </spurce>
2 같이 보기
3 참고
편집자 Jmnote Jmnote bot
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