library("gamlss2")
m <- gamlss2(mstatus ~ s(age) | . | ., data = marital.nz, family = MN(4))
plot(m)
par <- predict(m)
probs <- family(m)$probabilities(par)
names(probs) <- levels(marital.nz$mstatus)
i <- order(marital.nz$age)
matplot(marital.nz$age[i], probs[i, ], type = "l", lty = 1, lwd = 2,
xlab = "Age", ylab = "Probabilities")
legend("center", names(probs), lty = 1, lwd = 2, col = 1:4)Multinomial Logit Family
Description
The MN() family implements a multinomial logit model for categorical responses with \(k \ge 2\) unordered categories.
Usage
MN(k)
Arguments
k
|
An integer specifying the number of response categories. |
Details
The response must be a factor with exactly k levels. The first level is treated as the reference category.
For categories \(j = 2, \ldots, k\), each predictor models the log-odds relative to the reference category.
The family provides analytical first and second derivatives of the log-likelihood with respect to the predictors and a probabilities() method for fitted category probabilities.
Value
A “gamlss2.family” object to be used with gamlss2.
See Also
gamlss2, gamlss2.family