coef.logitchoice: Return estimated coefficients from fitted logitchoice object.

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

Description

Returns the model coefficients for each lambda.

Usage

## S3 method for class 'logitchoice'
coef(object, lambdaIndex = NULL, ...)

Arguments

object	Fitted "logitchoice" model object.
lambdaIndex	Index of lambda value at which to extract coefficients. If NULL, return the coefficients for all values of lambda in the path.
...	Not used.

Details

Returns the actual main effect and interaction coefficients. These satisfy the sum constraints in the original linear interaction model.

Value

A matrix of dimension nvars x length(lambdaIndex).

Author(s)

Michael Lim and
Maintainer: Michael Lim [e-mail]

See Also

predict.logitchoice, 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$betahat - coef(fit)))

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