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Bayesian influence diagnostics using normalized functional Bregman divergence
Communications in Statistics - Theory and Methods ( IF 0.6 ) Pub Date : 2020-05-18 , DOI: 10.1080/03610926.2020.1764583 Ian M. Danilevicz 1 , Ricardo S. Ehlers 2
Communications in Statistics - Theory and Methods ( IF 0.6 ) Pub Date : 2020-05-18 , DOI: 10.1080/03610926.2020.1764583 Ian M. Danilevicz 1 , Ricardo S. Ehlers 2
Affiliation
Ideally, any statistical inference should be robust to local influences. Although there are simple ways to check about leverage points in independent and linear problems, more complex models requir...
中文翻译:
使用归一化功能 Bregman 散度进行贝叶斯影响诊断
理想情况下,任何统计推断都应该对局部影响具有鲁棒性。尽管有简单的方法可以检查独立和线性问题中的杠杆点,但更复杂的模型需要...
更新日期:2020-05-18
中文翻译:
使用归一化功能 Bregman 散度进行贝叶斯影响诊断
理想情况下,任何统计推断都应该对局部影响具有鲁棒性。尽管有简单的方法可以检查独立和线性问题中的杠杆点,但更复杂的模型需要...