How the Choice of Distance Measure Influences the Detection of Prior-Data Conflict

被引:6
|
作者
Lek, Kimberley [1 ]
Van De Schoot, Rens [1 ,2 ]
机构
[1] Univ Utrecht, Dept Methods & Stat, NL-3584 CH Utrecht 14, Netherlands
[2] North West Univ, Fac Humanities, Optentia Res Program, ZA-1900 Vanderbijlpark, South Africa
来源
ENTROPY | 2019年 / 21卷 / 05期
关键词
prior-data conflict; distance measure; Kullback-Leibler; data agreement criterion;
D O I
10.3390/e21050446
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The present paper contrasts two related criteria for the evaluation of prior-data conflict: the Data Agreement Criterion (DAC; Bousquet, 2008) and the criterion of Nott et al. (2016). One aspect that these criteria have in common is that they depend on a distance measure, of which dozens are available, but so far, only the Kullback-Leibler has been used. We describe and compare both criteria to determine whether a different choice of distance measure might impact the results. By means of a simulation study, we investigate how the choice of a specific distance measure influences the detection of prior-data conflict. The DAC seems more susceptible to the choice of distance measure, while the criterion of Nott et al. seems to lead to reasonably comparable conclusions of prior-data conflict, regardless of the distance measure choice. We conclude with some practical suggestions for the user of the DAC and the criterion of Nott et al.
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页数:17
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