Profile Likelihood in Directed Graphical Models from BUGS Output

Malene Højbjerre
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, PMLR R3:123-128, 2001.

Abstract

This paper presents a method for using output of the computer program BUGS to obtain approximate profile likelihood functions of parameters or functions of parameters in directed graphical models with incomplete data. The method also provides a tool to approximate integrated likelihood functions. The prior distributions specified in BUGS do not have a significant impact on the profile likelihood functions and we consider the method as a desirable supplement to BUGS that enables us to do both Bayesian and likelihood based analyses in directed graphical models.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR3-hojbjerre01a, title = {Profile Likelihood in Directed Graphical Models from {BUGS} Output}, author = {H{\o}jbjerre, Malene}, booktitle = {Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics}, pages = {123--128}, year = {2001}, editor = {Richardson, Thomas S. and Jaakkola, Tommi S.}, volume = {R3}, series = {Proceedings of Machine Learning Research}, month = {04--07 Jan}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/r3/hojbjerre01a/hojbjerre01a.pdf}, url = {https://proceedings.mlr.press/r3/hojbjerre01a.html}, abstract = {This paper presents a method for using output of the computer program BUGS to obtain approximate profile likelihood functions of parameters or functions of parameters in directed graphical models with incomplete data. The method also provides a tool to approximate integrated likelihood functions. The prior distributions specified in BUGS do not have a significant impact on the profile likelihood functions and we consider the method as a desirable supplement to BUGS that enables us to do both Bayesian and likelihood based analyses in directed graphical models.}, note = {Reissued by PMLR on 31 March 2021.} }
Endnote
%0 Conference Paper %T Profile Likelihood in Directed Graphical Models from BUGS Output %A Malene Højbjerre %B Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 2001 %E Thomas S. Richardson %E Tommi S. Jaakkola %F pmlr-vR3-hojbjerre01a %I PMLR %P 123--128 %U https://proceedings.mlr.press/r3/hojbjerre01a.html %V R3 %X This paper presents a method for using output of the computer program BUGS to obtain approximate profile likelihood functions of parameters or functions of parameters in directed graphical models with incomplete data. The method also provides a tool to approximate integrated likelihood functions. The prior distributions specified in BUGS do not have a significant impact on the profile likelihood functions and we consider the method as a desirable supplement to BUGS that enables us to do both Bayesian and likelihood based analyses in directed graphical models. %Z Reissued by PMLR on 31 March 2021.
APA
Højbjerre, M.. (2001). Profile Likelihood in Directed Graphical Models from BUGS Output. Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research R3:123-128 Available from https://proceedings.mlr.press/r3/hojbjerre01a.html. Reissued by PMLR on 31 March 2021.

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