predict.logitchoice: Make predictions from a "logitchoice" object.

In logitchoice: Fitting l2-regularized logit choice models via generalized gradient descent

Description

Similar to other predict methods, this function returns fitted values on the response scale.

Usage

## S3 method for class 'logitchoice'
predict(object, X, grouping, lambda=NULL, ...)

Arguments

object	Fitted "logitchoice" model object.
X	Matrix of new values for which to make predictions. Must have the same number of variables as during training the model.
grouping	Grouping information for choice situations as in logitchoice.
lambda	User input lambda sequence. Must be subset of the lambdas used in fitting. If NULL (the default), predict at all the lambdas used during fitting.
...	Not used. Other arguments to predict.

Details

If lambda is not specified, makes predictions at all the fitted lambda values. Users may provide their own lambda sequence, but this must be a subset of the values used to fit the models.

Value

A matrix of predicted values, with columns corresponding to each fitted model.

Author(s)

Michael Lim
Maintainer: Michael Lim [e-mail]

See Also

logitchoice, predict.logitchoice

Examples

  groupSizes = sample(6:18, 100, replace=TRUE)
  numGroups = length(groupSizes)
  n = sum(groupSizes)
  p = 10
  X = matrix(rnorm(n*p), nrow=n)
  X = scale(X)
  Y = rep(0, n)
  Y[cumsum(groupSizes)] = 1
  grouping = rep(1:numGroups, groupSizes)
  fit = logitchoice(X, Y, grouping)
max(abs(fit$yhat - predict(fit, X, grouping)))

logitchoice documentation built on May 29, 2017, 11:56 a.m.