augment.logitr

Glance a <code>logitr</code> class object

Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) <doi:10.1017/CBO9780511805271>. More details can be found in Helveston (2023) <doi:10.18637/jss.v105.i10>.

John Helveston

logitr

Logit Models w/Preference & WTP Space Utility Parameterizations

Connor Forsythe

augment.logitr function

<dl><dt>x</dt>
<dd>is an object of class <code>logitr</code>.</dd>
<dt>newdata</dt>
<dd>a <code>data.frame</code>. Each row is an alternative and each column an
attribute corresponding to parameter names in the estimated model. Defaults
to <code>NULL</code>, in which case predictions are made on the original data used to
estimate the model.</dd>
<dt>obsID</dt>
<dd>The name of the column that identifies each set of
alternatives in the data. Required if newdata != NULL. Defaults to <code>NULL</code>,
in which case the value for <code>obsID</code> from the data in <code>object</code> is used.</dd>
<dt>type</dt>
<dd>A character vector defining what to predict: <code>prob</code> for
probabilities, <code>outcomes</code> for outcomes. If you want both outputs, use
<code>c("prob", "outcome")</code>. Outcomes are predicted randomly according to the
predicted probabilities. Defaults to <code>"prob"</code>.</dd>
<dt>...</dt>
<dd>further arguments.</dd></dl>

Arguments

Glance a logitr class object — augment.logitr

<dl>

<dt>x</dt>
<dd>is an object of class <code>logitr</code>.</dd>


<dt>newdata</dt>
<dd>a <code>data.frame</code>. Each row is an alternative and each column an
attribute corresponding to parameter names in the estimated model. Defaults
to <code>NULL</code>, in which case predictions are made on the original data used to
estimate the model.</dd>


<dt>obsID</dt>
<dd>The name of the column that identifies each set of
alternatives in the data. Required if newdata != NULL. Defaults to <code>NULL</code>,
in which case the value for <code>obsID</code> from the data in <code>object</code> is used.</dd>


<dt>type</dt>
<dd>A character vector defining what to predict: <code>prob</code> for
probabilities, <code>outcomes</code> for outcomes. If you want both outputs, use
<code>c("prob", "outcome")</code>. Outcomes are predicted randomly according to the
predicted probabilities. Defaults to <code>"prob"</code>.</dd>


<dt>...</dt>
<dd>further arguments.</dd>

</dl>

augment.logitr: Glance a `logitr` class object

Description

Usage

Value

Arguments

Examples