Journal article
A robust bayes factor for linear models
Australian and New Zealand Journal of Statistics, Vol.47(4), pp.449-462
2005
Abstract
This paper proposes a new robust Bayes factor for comparing two linear models. The factor is based on a pseudo-model for outliers and is more robust to outliers than the Bayes factor based on the variance-inflation model for outliers. If an observation is considered an outlier for both models this new robust Bayes factor equals the Bayes factor calculated after removing the outlier. If an observation is considered an outlier for one model but not the other then this new robust Bayes factor equals the Bayes factor calculated without the observation, but a penalty is applied to the model considering the observation as an outlier. For moderate outliers where the variance-inflation model is suitable, the two Bayes factors are similar. The new Bayes factor uses a single robustness parameter to describe a priori belief in the likelihood of outliers. Real and synthetic data illustrate the properties of the new robust Bayes factor and highlight the inferior properties of Bayes factors based on the variance-inflation model for outliers.
Details
- Title
- A robust bayes factor for linear models
- Authors/Creators
- R.H. Taplin (Author/Creator) - Murdoch University
- Publication Details
- Australian and New Zealand Journal of Statistics, Vol.47(4), pp.449-462
- Publisher
- Blackwell Publishing
- Identifiers
- 991005540084507891
- Copyright
- © 2005 Australian Statistical Publishing Association Inc.
- Murdoch Affiliation
- School of Chemical and Mathematical Science
- Language
- English
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Metrics
61 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Citation topics
- 9 Mathematics
- 9.92 Statistical Methods
- 9.92.220 Robust Estimation
- Web Of Science research areas
- Statistics & Probability
- ESI research areas
- Mathematics