dataQualiN

This is data set with qualitative nominal variables containing 500 obs
extracted from ASIA Bayesian Networks of bnlearn package repository.

datasets

This project aims to enable the method of Path Analysis to infer causalities
from data. For this we propose a hybrid approach, which uses Bayesian network
structure learning algorithms from data to create the input file for creation of a
PA model. The process is performed in a semi-automatic way by our intermediate
algorithm, allowing novice researchers to create and evaluate their own PA models
from a data set. The references used for this project are:
Koller, D., & Friedman, N. (2009). Probabilistic graphical models: principles and techniques. MIT press. <doi:10.1017/S0269888910000275>.
Nagarajan, R., Scutari, M., & L<c3><a8>bre, S. (2013). Bayesian networks in r. Springer, 122, 125-127. Scutari, M., & Denis, J. B. <doi:10.1007/978-1-4614-6446-4>.
Scutari M (2010). Bayesian networks: with examples in R. Chapman and Hall/CRC. <doi:10.1201/b17065>.
Rosseel, Y. (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1 - 36. <doi:10.18637/jss.v048.i02>.

Elias Carvalho

bnpa

Bayesian Networks & Path Analysis

dataQualiN function

A data frame with 500 rows and 7 variables:<dl class="dl-horizontal">
 <dt>A</dt><dd>a categorical variale</dd>
 <dt>S</dt><dd>a categorical variale</dd>
 <dt>T</dt><dd>a categorical variale</dd>
 <dt>L</dt><dd>a categorical variale</dd>
 <dt>B</dt><dd>a categorical variale</dd>
 <dt>E</dt><dd>a categorical variale</dd>
 <dt>X</dt><dd>a categorical variale</dd>
 <dt>D</dt><dd>a categorical variale</dd>
 ...
</dl>

Format

A qualitative data set to test functions — dataQualiN

A data frame with 500 rows and 7 variables:<dl class='dl-horizontal'>
 <dt>A</dt><dd>a categorical variale</dd>
 <dt>S</dt><dd>a categorical variale</dd>
 <dt>T</dt><dd>a categorical variale</dd>
 <dt>L</dt><dd>a categorical variale</dd>
 <dt>B</dt><dd>a categorical variale</dd>
 <dt>E</dt><dd>a categorical variale</dd>
 <dt>X</dt><dd>a categorical variale</dd>
 <dt>D</dt><dd>a categorical variale</dd>
 ...
</dl>

dataQualiN: A qualitative data set to test functions

Description

Usage

Arguments

Format