Bayesian Diagnostics

实际计量经济学分析中发生的主要变化之一是 是越来越多地使用诊断统计数据， 批评计量经济学模型，并鼓励模型的修订。 使用 对统计理论提出了挑战， 经典或贝叶斯。 传统的统计理论处理 评估对假设数据集的计划响应。 确实 如果没有一组计划，就不可能计算抽样属性 指示对每个可想到的数据集的数据的响应。 使用诊断统计量来评价模型是一种进步 宣布计划中的应对措施尚未完全承诺， 当观察到实际数据时进行修订。 该项目的目的是编制诊断统计数据。 大部分精力将用于启发诊断，但也有一些 批评工作也要做好。 方法将是贝叶斯。 在拟订诱导法方面已经取得了进展 变量选择问题的诊断。 此扩展 将着手处理其他严重的统计问题 如异方差性、非正态性和序列相关性。 这 这项工作是重要的，因为它将更好的方法来估计 经济关系。

One of the major changes taking place in practical econometric analysis is the increasing use of diagnostic statistics which are used to critique econometric models and to stimulate model revisions. The use of diagnostic statistics presents a challenge to statistical theory, classical or Bayesian. Traditional statistical theory deals with the evaluation of planned responses to hypothetical data sets. Indeed, it is impossible to compute sampling properties without a set of plans indicating the response to the data for every conceivable data set. The use of a diagnostic statistic to criticize a model is an advance announcement that the planned response is not fully committed and may be revised when the actual data are observed. The purpose of this project is to formulate diagnostic statistics. Most of the effort will be devoted to elicitation diagnostics, but some work well also be done on criticisms. The approach will be Bayesian. Progress has already been made on the formulation of elicitation diagnostics for the problem of choice of variables. Extensions of this work will be undertaken to deal with other serious statistical problems such as heteroscedasticity, nonnormality and serial correlation. This work is important because it will better methods for estimating economic relationships.