predict_hpaML

object

<p>An optional data frame (for <a rd-options="hpa" href="/link/hpaBinary?package=hpa&version=1.1.3&to=hpa" data-mini-rdoc="hpa::hpaBinary">hpaBinary</a> and
<a rd-options="hpa" href="/link/hpaSelection?package=hpa&version=1.1.3&to=hpa" data-mini-rdoc="hpa::hpaSelection">hpaSelection</a>) or numeric matrix (for <a rd-options="hpa" href="/link/hpaML?package=hpa&version=1.1.3&to=hpa" data-mini-rdoc="hpa::hpaML">hpaML</a>)
in which to look for variables with which to predict. If omitted,
the original data frame (matrix) used.</p>

newdata

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_hpaML function

<p>An optional data frame (for <a rd-options='hpa' href='hpaBinary'>hpaBinary</a> and
<a rd-options='hpa' href='hpaSelection'>hpaSelection</a>) or numeric matrix (for <a rd-options='hpa' href='hpaML'>hpaML</a>)
in which to look for variables with which to predict. If omitted,
the original data frame (matrix) used.</p>

predict_hpaML: Predict method for hpaML

Description

Usage

Arguments

Value