Train

A sample of 235 Dutch individuals facing 2929 choice situations

datasets

Maximum likelihood estimation of random utility discrete
choice models. The software is described in Croissant (2020)
<doi:10.18637/jss.v095.i11> and the underlying methods in
Train (2009) <doi:10.1017/CBO9780511805271>.

Yves Croissant

mlogit

Multinomial Logit Models

Train function

A dataframe containing:
- id: individual identifient,
- choiceid: choice identifient,
- choice: one of 'A' or 'B',
- price_z: price of proposition z (z = 'A', 'B') in cents of
guilders,
- time_z: travel time of proposition z (z = 'A', 'B') in
minutes,
- comfort_z: comfort of proposition z (z = 'A', 'B'), 0, 1 or
2 in decreasing comfort order,
- change_z: number of changes for proposition z (z = 'A', 'B').

Train: Stated Preferences for Train Traveling

Description

Arguments

Format

References