Overview of Bounded Support Distributions and Methods for Bayesian Treatment of Industrial Data
Kamil Dedecius, Pavel Ettler
2013
Abstract
Statistical analysis and modelling of various phenomena are well established in nowadays industrial practice. However, the traditional approaches neglecting the true properties of the phenomena still dominate. Among others, this includes also the cases when a variable with bounded range is analyzed using probabilistic distributions with unbounded domain. Since many of those variables nearly fulfill the basic conditions imposed by the chosen distribution, the properties of used statistical models are violated rather rarely. Still, there are numerous cases, when inference with distributions with unbounded domain may lead to absurd conclusions. This paper addresses this issue from the Bayesian viewpoint. It briefly discusses suitable distributions and inferential methods overcoming the emerging computational issues.
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in Harvard Style
Dedecius K. and Ettler P. (2013). Overview of Bounded Support Distributions and Methods for Bayesian Treatment of Industrial Data . In Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-70-9, pages 380-387. DOI: 10.5220/0004439003800387
in Bibtex Style
@conference{icinco13,
author={Kamil Dedecius and Pavel Ettler},
title={Overview of Bounded Support Distributions and Methods for Bayesian Treatment of Industrial Data},
booktitle={Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2013},
pages={380-387},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004439003800387},
isbn={978-989-8565-70-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Overview of Bounded Support Distributions and Methods for Bayesian Treatment of Industrial Data
SN - 978-989-8565-70-9
AU - Dedecius K.
AU - Ettler P.
PY - 2013
SP - 380
EP - 387
DO - 10.5220/0004439003800387