Entropy | |
How the Choice of Distance Measure Influences the Detection of Prior-Data Conflict | |
Kimberley Lek1  Rens Van De Schoot1  | |
[1] Department of Methods and Statistics, Utrecht University, 3584 CH 14 Utrecht, The Netherlands; | |
关键词: prior-data conflict; distance measure; Kullback-Leibler; data agreement criterion; | |
DOI : 10.3390/e21050446 | |
来源: DOAJ |
【 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.
【 授权许可】
Unknown