library(ordinal)
data(wine)
## clm.fit with nominal and scale effects:
## get simple model:
fm1 <- clm(rating ~ temp, scale=~temp, nominal=~ contact,
data=wine, method="design")
str(fm1, give.attr=FALSE)
fm1$control$method <- "Newton"
res <- clm.fit(fm1)
names(res)
res$Theta
## construct some weights and offsets:
set.seed(1)
off1 <- runif(length(fm1$y))
set.seed(1)
off2 <- rnorm(length(fm1$y))
set.seed(1)
wet <- runif(length(fm1$y))
## Fit various models:
fit <- clm.fit(fm1$y, fm1$X, fm1$S, fm1$NOM, weights=wet)
Coef <-
c(-0.905224120279548, 1.31043498891987, 3.34235590523008,
4.52389661722693, -3.03954652971192, -1.56922389038976,
-1.75662549320839, -1.16845464236365, 2.52988580848393,
-0.0261457032829033)
stopifnot(all.equal(coef(fit), Coef, check.attributes=FALSE, tol=1e-6))
str(fit)
fit <- clm.fit(fm1$y, fm1$X, fm1$S, fm1$NOM, offset=off1)
str(fit)
fit <- clm.fit(fm1$y, fm1$X, fm1$S, fm1$NOM, offset=off1,
S.offset=off2)
str(fit)
fit <- clm.fit(fm1$y, fm1$X, fm1$S)
str(fit)
fit <- clm.fit(fm1$y, fm1$X)
str(fit)
fit <- clm.fit(fm1$y)
coef(fit)
str(fit)
## Remember: compare with corresponding .Rout file
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