coef.ordinalNet

object

Logical. If <code>TRUE</code>, coefficient estimates are returned in
matrix form. Otherwise a vector is returned.

matrix

Optional index number of the desired <code>lambda</code> within
the sequence of <code>lambdaVals</code>. By default, the solution with the best AIC
is returned.

whichLambda

Selects the best <code>lambda</code> value by AIC or BIC. Only used
if <code>whichLambda=NULL</code>.

criteria

Not used. Additional coef arguments.

Method to extract fitted coefficients from an "ordinalNet" object.

Fits ordinal regression models with elastic net penalty.
Supported model families include cumulative probability, stopping ratio,
continuation ratio, and adjacent category. These families are a subset of
vector glm's which belong to a model class we call the elementwise link
multinomial-ordinal (ELMO) class. Each family in this class links a vector
of covariates to a vector of class probabilities. Each of these families
has a parallel form, which is appropriate for ordinal response data, as
well as a nonparallel form that is appropriate for an unordered categorical
response, or as a more flexible model for ordinal data. The parallel model
has a single set of coefficients, whereas the nonparallel model has a set of
coefficients for each response category except the baseline category. It is
also possible to fit a model with both parallel and nonparallel terms, which
we call the semi-parallel model. The semi-parallel model has the flexibility
of the nonparallel model, but the elastic net penalty shrinks it toward the
parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2021)
<doi:10.18637/jss.v099.i06>.

coef.ordinalNet: Method to extract fitted coefficients from an "ordinalNet" object.

Description

Usage

Arguments

Value

See Also

Examples