Philosophy and the practice of Bayesian statistics.
Philosophy and the practice of Bayesian statistics.
复制标题
DOI：
10.1111/j.2044-8317.2011.02037.x
复制
发表时间：
2013-02
期刊：
影响因子：
--
通讯作者：
Shalizi CR
中科院分区：
文献类型：
--
作者：
Gelman A;Shalizi CR
科学哲学中的一个重要学派将贝叶斯推理与归纳推理甚至合理性等同起来，并且似乎因贝叶斯统计的兴起和实际成功而得到加强。我们认为，最成功的形式贝叶斯统计实际上并不支持这种特定的哲学，而是雅阁更好地与复杂形式的假设演绎。我们研究先验分布在贝叶斯模型中所起的实际作用，以及模型检查和模型修正的关键方面，这些方面超出了贝叶斯确认理论的范围。我们利用文献的一致性贝叶斯更新，也对我们的经验，在社会科学中的应用工作。对这些问题的澄清不仅有利于科学哲学，也有利于统计实践。最好的情况是，归纳主义的观点鼓励研究人员在不检查模型的情况下拟合和比较模型;最坏的情况是，理论家积极阻止实践者进行模型检查，因为它不适合他们的框架。
A substantial school in the philosophy of science identifies Bayesian inference with inductive inference and even rationality as such, and seems to be strengthened by the rise and practical success of Bayesian statistics. We argue that the most successful forms of Bayesian statistics do not actually support that particular philosophy but rather accord much better with sophisticated forms of hypothetico-deductivism. We examine the actual role played by prior distributions in Bayesian models, and the crucial aspects of model checking and model revision, which fall outside the scope of Bayesian confirmation theory. We draw on the literature on the consistency of Bayesian updating and also on our experience of applied work in social science. Clarity about these matters should benefit not just philosophy of science, but also statistical practice. At best, the inductivist view has encouraged researchers to fit and compare models without checking them; at worst, theorists have actively discouraged practitioners from performing model checking because it does not fit into their framework.
登录
查看更多内容
影响因子：
3.7
作者：
Bayarri, MJ;Berger, JO
通讯作者：
Berger, JO
DOI：
10.2307/2982063
发表时间：
1980-01-01
影响因子：
2
作者：
BOX, GEP
通讯作者：
BOX, GEP
影响因子：
3.7
作者：
BERGER, JO;SELLKE, T
通讯作者：
SELLKE, T
影响因子：
5.7
作者：
Bayarri, M. J.;Castellanos, M. E.
通讯作者：
Castellanos, M. E.
影响因子：
--
作者：
BERK, RH
通讯作者：
BERK, RH