Usage
multinom(formula, data, weights, subset, na.action,
contrasts = NULL, Hess = FALSE, summ = 0, censored = FALSE,
model = FALSE, ...)Arguments
formula
a formula expression as for regression models, of the form
response ~ predictors. The response should be a factor or a
matrix with K columns, which will be interpreted as counts for each of
K classes.
A log-linear model is fitted, with coeffi
data
an optional data frame in which to interpret the variables occurring
in formula.
weights
optional case weights in fitting.
subset
expression saying which subset of the rows of the data should be used
in the fit. All observations are included by default.
na.action
a function to filter missing data.
contrasts
a list of contrasts to be used for some or all of
the factors appearing as variables in the model formula.
Hess
logical for whether the Hessian (the observed/expected information matrix)
should be returned.
summ
integer; if non-zero summarize by deleting duplicate rows and adjust weights.
Methods 1 and 2 differ in speed (2 uses C); method 3 also combines rows
with the same X and different Y, which changes the baseline for the
deviance.
censored
If Y is a matrix with K > 2 columns, interpret the entries as one
for possible classes, zero for impossible classes, rather than as
counts.
model
logical. If true, the model frame is saved as component model
of the returned object.
...
additional arguments for nnet