asMTEString

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

parameters

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

This function builds a string with the structure of a <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. P<c3><a9>rez-Bernab<c3><a9>, A. Salmer<c3><b3>n, H. Langseth (2015) <doi:10.1007/978-3-319-20807-7_36>; H. Langseth, T.D. Nielsen, I. P<c3><a9>rez-Bernab<c3><a9>, A. Salmer<c3><b3>n (2014) <doi:10.1016/j.ijar.2013.09.012>; I. P<c3><a9>rez-Bernab<c3><a9>, A. Fern<c3><a1>ndez, R. Rum<c3><ad>, A. Salmer<c3><b3>n (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'.

asMTEString: Parameters to MTE String

Description

Usage

Arguments

Value

Examples