Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data
Bayesian Inference for Partially Identified Models: Exploring the Limits of Limited Data
复制标题
部分识别模型的贝叶斯推理：探索有限数据的局限性
DOI：
10.1201/b18308
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发表时间：
2015
影响因子：
3.8
通讯作者：
P. Gustafson
中科院分区：
文献类型：
--
作者：
P. Gustafson
什么对我们不利？什么是给我们的？部分识别模型的一些简单例子部分识别模型的推理结构贝叶斯推理后验分布结构PIMs计算策略贝叶斯更新强度重新考察后验矩可信区间评估推理部分识别与模型错配的价值识别的警铃比较反映不确定性的偏差一个进一步的例子PIM与IPMM模型涉及错分类的其他研究二元到三元错分类二元错分类跨三个种群模型涉及工具变量什么是工具变量？不完全顺应性建模一个近似的工具变量进一步的例子推断面对隐藏的亚种群生态推断，进一步的主题重新审视计算考虑研究设计考虑应用结论性思想别人说了什么？前面的路是什么？指数
Introduction Identification What Is against Us? What Is for Us? Some Simple Examples of Partially Identified Models The Road Ahead The Structure of Inference in Partially Identified Models Bayesian Inference The Structure of Posterior Distributions in PIMs Computational Strategies Strength of Bayesian Updating, Revisited Posterior Moments Credible Intervals Evaluating the Worth of Inference Partial Identification versus Model Misspecification The Siren Call of Identification Comparing Bias Reflecting Uncertainty A Further Example Other Investigations of PIM versus IPMM Models Involving Misclassification Binary to Trinary Misclassification Binary Misclassification across Three Populations Models Involving Instrumental Variables What Is an Instrumental Variable? Imperfect Compliance Modeling an Approximate Instrumental Variable Further Examples Inference in the Face of a Hidden Subpopulation Ecological Inference, Revisited Further Topics Computational Considerations Study Design Considerations Applications Concluding Thoughts What Have Others Said? What Is the Road ahead? Index