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>.

Random Coefficient Binary Response Estimation

package-ubuntu-20.04-r-4.0.5#cran#RCBR-0.5.9

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

## S3 method for class 'GK'
predict(object, ...)

<table summary="R argblock">
<tr valign="top">
<td><code>object</code></td>
<td>
<p>is the fitted object of class "GK"</p>
</td>
</tr>
<tr valign="top">
<td><code>...</code></td>
<td>
<p>is expected to contain an argument <code>newdata</code></p>
</td>
</tr>
</table>

<p>a vector pf predicted probabilities
</p>

package-ubuntu-20.04-r-4.0.5#cran#RCBR-0.5.9#docs#predict.GK

`object`	is the fitted object of class "GK"
`...`	is expected to contain an argument `newdata`

predict.GK

Description

Usage

Arguments

Value

RCBR

We don't support your browser anymore