is.motbf

is.univmotbf

is.jointmotbf

is.motbf_fit

is.motbf_fit_cv

is.mte

is.mop

subclass

Utility functions to check whether an object belongs to a specific MoTBF class, or to identify its underlying subclass (<code>'mop'</code> or <code>'mte'</code>).

Learning, manipulation and evaluation of mixtures of truncated basis functions
(MoTBFs), which include mixtures of polynomials (MOPs) and mixtures of truncated
exponentials (MTEs). MoTBFs are a flexible framework for modelling hybrid Bayesian
networks (I. Pérez-Bernabé, A. Salmerón, H. Langseth (2015) <doi:10.1007/978-3-319-20807-7_36>; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) <doi:10.1016/j.ijar.2013.09.012>; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) <doi:10.1007/s10618-015-0429-7>). The package provides functionality for learning univariate, multivariate and conditional densities, with the possibility of incorporating prior knowledge. Structural learning of hybrid Bayesian networks is also provided. A set of useful tools is provided, including plotting, printing and likelihood evaluation. This package makes use of S3 objects, with two new classes called 'motbf' and 'jointmotbf'.

Ana D. Maldonado

MoTBFs

Learning Hybrid Bayesian Networks using Mixtures of Truncated
Basis Functions

Inmaculada Pérez-Bernabé

Antonio Salmerón

Thomas D.  Nielsen

Ángel T.  Sáez-Ruiz

is.motbf function

<dl><dt>x</dt>
<dd>An object to be checked.</dd>
<dt>class</dt>
<dd>Character string specifying the target class name.</dd>
<dt>fx</dt>
<dd>An object to determine the subclass for.</dd></dl>

Arguments

Check MoTBF Classes and Subclasses — is.motbf

<dl>

<dt>x</dt>
<dd>An object to be checked.</dd>


<dt>class</dt>
<dd>Character string specifying the target class name.</dd>


<dt>fx</dt>
<dd>An object to determine the subclass for.</dd>

</dl>

Check MoTBF Classes and Subclasses

is.motbf: Check MoTBF Classes and Subclasses

Description

Usage

Value

Arguments