标题： 可诱发性 显示英文标题

标题： Elicitability

摘要： 一个分析师被指派进行一项统计研究。 该分析师未受到监督，能够操控研究。 他可以根据其报告获得报酬，并信任从独立来源收集的数据，这些数据被建模为一个统计实验。 我们描述了通过适当设计的激励措施可以引出的信息，并将我们的框架应用于各种常见的统计模型。 然后，我们根据它们能够引出的信息来比较实验。 这种顺序与Blackwell顺序相关，但有所不同。 用于估计的数据也更受引出信息的青睐，但反之则不成立。 我们的结果揭示了在支付方案中使用数据作为激励生成器与使用数据进行统计推断之间的差异。 显示英文摘要

摘要： An analyst is tasked with producing a statistical study. The analyst is not monitored and is able to manipulate the study. He can receive payments contingent on his report and trusted data collected from an independent source, modeled as a statistical experiment. We describe the information that can be elicited with appropriately shaped incentives, and apply our framework to a variety of common statistical models. We then compare experiments based on the information they enable us to elicit. This order is connected to, but different from, the Blackwell order. Data preferred for estimation are also preferred for elicitation, but not conversely. Our results shed light on how using data as incentive generator in payment schemes differs from using data for statistical inference.