returns the proposed /nbn/ with a new topological order without
modifying the joint distribution of all variables.

This allows to
directly find regression formulae within the Gaussian Bayesian
networks.

1 | ```
nbn2nbn(nbn, norder)
``` |

`nbn` |
The /nbn/ to transform. |

`norder` |
The topological order to follow. It can be indicated by names or numbers. When not all nodes are included, the resulting /nbn/ is restricted to these nodes after marginalization. |

BE aware that for the moment, no check is made about the topological order and if it is not, the result is FALSE!

The resulting /nbn/.

1 2 3 4 5 | ```
print8mn(nbn2mn(rbmn0nbn.01, algo=1));
print8mn(nbn2mn(rbmn0nbn.01, algo=2));
print8mn(nbn2mn(rbmn0nbn.01, algo=3));
print8mn(nbn2mn(nbn2nbn(rbmn0nbn.02, c(1, 2, 4, 5, 3))));
print8mn(nbn2mn(nbn2nbn(rbmn0nbn.02, c(4, 1, 2, 3, 5))));
``` |

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