clm
.
This makes it possible to use e.g.
update(obj, location = ~ . - var1, scale = ~ . + var2)
## S3 method for class 'clm':
update(object, formula., location, scale, nominal,...,
evaluate = TRUE)
## S3 method for class 'clmm':
update(object, formula., location, scale, nominal,...,
evaluate = TRUE)
clm
object.update.formula
for details.update.formula
for details.update.formula
for details.evaluate = TRUE
the fitted object is returned,
otherwise the updated call.options(contrasts = c("contr.treatment", "contr.poly"))
data(soup)
m1 <- clm(SURENESS ~ PROD, scale = ~PROD, data = soup,
link = "logistic")
m2 <- update(m1, link = "probit")
m3 <- update(m1, link = "cloglog")
m4 <- update(m1, link = "loglog")
anova(m1, update(m1, scale = ~.-PROD))
mT1 <- update(m1, threshold = "symmetric")
## Fit model from polr example:
data(housing, package = "MASS")
fm1 <- clm(Sat ~ Infl + Type + Cont, weights = Freq, data = housing)
update(fm1, location = ~ . - Type, scale =~ Cont)
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