predict.GK

Given a fitted model by the Gautier Kitamura procedure predictions are made
at new design points given by the <code>newdata</code> argument.

Nonparametric maximum likelihood estimation methods
for random coefficient binary response models and some related
functionality for sequential processing of hyperplane arrangements.
See J. Gu and R. Koenker (2020) <DOI:10.1080/01621459.2020.1802284>.

Roger Koenker

RCBR

Random Coefficient Binary Response Estimation

Jiaying Gu

predict.GK function

<dl><dt>object</dt>
<dd>is the fitted object of class "GK"</dd>
<dt>...</dt>
<dd>is expected to contain an argument <code>newdata</code></dd></dl>

Arguments

Prediction of Marginal Effects — predict.GK

<dl>

<dt>object</dt>
<dd>is the fitted object of class "GK"</dd>


<dt>...</dt>
<dd>is expected to contain an argument <code>newdata</code></dd>

</dl>

predict.GK: Prediction of Marginal Effects

Description

Usage

Value

Arguments