predict_hpaBinary

Multivariate conditional and marginal densities, moments, cumulative distribution functions as well as binary choice and sample selection models based on Hermite polynomial approximation which was proposed and described by A. Gallant and D. W. Nychka (1987) <doi:10.2307/1913241>.

Potanin Bogdan

Distributions Hermite Polynomial Approximation

predict_hpaBinary function

<dl><dt>object</dt>
<dd>Object of class "hpaBinary"</dd>
<dt>newdata</dt>
<dd>An optional data frame (for hpaBinary and
hpaSelection) or numeric matrix (for hpaML)
in which to look for variables with which to predict. If omitted,
the original data frame (matrix) used.</dd>
<dt>is_prob</dt>
<dd>logical; if TRUE (default) 
then function returns predicted probabilities. 
Otherwise latent variable
(single index) estimates will be returned.</dd></dl>

Arguments

Predict method for hpaBinary — predict_hpaBinary

<dl>

<dt>object</dt>
<dd>Object of class "hpaBinary"</dd>


<dt>newdata</dt>
<dd>An optional data frame (for hpaBinary and
hpaSelection) or numeric matrix (for hpaML)
in which to look for variables with which to predict. If omitted,
the original data frame (matrix) used.</dd>


<dt>is_prob</dt>
<dd>logical; if TRUE (default) 
then function returns predicted probabilities. 
Otherwise latent variable
(single index) estimates will be returned.</dd>

</dl>

predict_hpaBinary: Predict method for hpaBinary

Description

Usage

Value

Arguments