Heating

A sample of 900 Californian households#'

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

Heating function

A dataframe containing:<ul>
<li>idcase: id,</li>
<li>depvar: heating system, one of gc (gas central), gr (gas room), ec
(electric central), er (electric room), hp (heat pump),</li>
<li>ic.z: installation cost for heating system z (defined for the
5 heating systems),</li>
<li>oc.z: annual operating cost for heating system z (defined for
the 5 heating systems),</li>
<li>pb.z: ratio oc.z/ic.z ,</li>
<li>income: annual income of the household,</li>
<li>agehed: age of the household head</li>
<li>rooms: numbers of rooms in the house,</li>
</ul>

Heating: Heating System Choice in California Houses

Description

Arguments

Format