An object-oriented Bayesian network for estimating mutation rates

A. Philip Dawid
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, PMLR R4:80-84, 2003.

Abstract

We describe the use of the object-oriented HUGIN 6 probabilistic expert system software to structure the problem of estimating mutation rates on the basis of family data when paternity can not be regarded as certain.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR4-dawid03a, title = {An object-oriented Bayesian network for estimating mutation rates}, author = {Dawid, A. Philip}, booktitle = {Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics}, pages = {80--84}, year = {2003}, editor = {Bishop, Christopher M. and Frey, Brendan J.}, volume = {R4}, series = {Proceedings of Machine Learning Research}, month = {03--06 Jan}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/r4/dawid03a/dawid03a.pdf}, url = {https://proceedings.mlr.press/r4/dawid03a.html}, abstract = {We describe the use of the object-oriented HUGIN 6 probabilistic expert system software to structure the problem of estimating mutation rates on the basis of family data when paternity can not be regarded as certain.}, note = {Reissued by PMLR on 01 April 2021.} }
Endnote
%0 Conference Paper %T An object-oriented Bayesian network for estimating mutation rates %A A. Philip Dawid %B Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 2003 %E Christopher M. Bishop %E Brendan J. Frey %F pmlr-vR4-dawid03a %I PMLR %P 80--84 %U https://proceedings.mlr.press/r4/dawid03a.html %V R4 %X We describe the use of the object-oriented HUGIN 6 probabilistic expert system software to structure the problem of estimating mutation rates on the basis of family data when paternity can not be regarded as certain. %Z Reissued by PMLR on 01 April 2021.
APA
Dawid, A.P.. (2003). An object-oriented Bayesian network for estimating mutation rates. Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research R4:80-84 Available from https://proceedings.mlr.press/r4/dawid03a.html. Reissued by PMLR on 01 April 2021.

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