asMTEString

This function builds a string with the structure of an <code>'mte'</code> function.

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

asMTEString function

<dl><dt>parameters</dt>
<dd>A <code>"numeric"</code> vector containing the coefficients.</dd>
<dt>num</dt>
<dd>A <code>"numeric"</code> value which contains the denominator of the coefficient
in the exponential.</dd></dl>

Arguments

Converting MTEs to strings — asMTEString

<dl>

<dt>parameters</dt>
<dd>A <code>"numeric"</code> vector containing the coefficients.</dd>


<dt>num</dt>
<dd>A <code>"numeric"</code> value which contains the denominator of the coefficient
in the exponential.</dd>

</dl>

asMTEString: Converting MTEs to strings

Description

Usage

Value

Arguments

Examples