Ordered Logistic or Probit Regression Model
Fit a logistic or probit regression model to an ordered factor response.
POLRModel(method = c("logistic", "probit", "loglog", "cloglog", "cauchit"))method |
logistic or probit or (complementary) log-log or cauchit (corresponding to a Cauchy latent variable). |
ordered
Further model details can be found in the source link below.
In calls to varimp for POLRModel, numeric argument
base may be specified for the (negative) logarithmic transformation of
p-values [defaul: exp(1)]. Transformed p-values are automatically
scaled in the calculation of variable importance to range from 0 to 100. To
obtain unscaled importance values, set scale = FALSE.
MLModel class object.
data(Boston, package = "MASS")
df <- within(Boston,
medv <- cut(medv,
breaks = c(0, 10, 15, 20, 25, 50),
ordered = TRUE))
fit(medv ~ ., data = df, model = POLRModel)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.