A design-based approximation to the Bayes Information Criterion in finite population sampling
In this article, various issues related to the implementation of the usual Bayesian Information Criterion (BIC) are critically examined in the context of modelling a finite population. A suitable design-based approximation to the BIC is proposed in order to avoid the derivation of the exact likeliho...
Main Authors: | Enrico Fabrizi, Parthasarathi Lahiri |
---|---|
Format: | Article |
Language: | English |
Published: |
University of Bologna
2014-05-01
|
Series: | Statistica |
Subjects: | |
Online Access: | http://rivista-statistica.unibo.it/article/view/4325 |
Similar Items
-
Sample size determination for Bayesian ANOVAs with informative hypotheses
by: Qianrao Fu, et al.
Published: (2022-11-01) -
Optimal Detection under the Restricted Bayesian Criterion
by: Shujun Liu, et al.
Published: (2017-07-01) -
Uncertainty Based Under-Sampling for Learning Naive Bayes Classifiers Under Imbalanced Data Sets
by: Christos K. Aridas, et al.
Published: (2020-01-01) -
Prior-based Bayesian information criterion
by: M. J. Bayarri, et al.
Published: (2019-01-01) -
Power Allocation and Low Complexity Detector for Differential Full Diversity Spatial Modulation Using Two Transmit Antennas
by: K. Dwarika, et al.
Published: (2017-06-01)