Reconciling Individual Probability Forecasts✱
Reconciling Individual Probability Forecasts✱
复制标题
协调个人概率预测â±
DOI：
10.1145/3593013.3593980
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Weinstein, Scott
中科院分区：
文献类型：
--
作者：
Roth, Aaron;Tolbert, Alexander;Weinstein, Scott
个体概率指的是只实现一次的结果的概率：明天下雨的概率，爱丽丝在未来12个月内死亡的概率，鲍勃在未来18个月内因暴力犯罪被捕的概率，等等。尽管如此，我们表明，双方同意的数据或如何从数据分布抽样不能同意不同意如何建模个人的概率。这是因为任何两个基本上不一致的个体概率模型都可以一起用来根据经验证伪和改进两个模型中的至少一个。这可以在一个“和解”过程中有效地迭代，从而产生双方都认为上级他们开始使用的模型的模型，并且这些模型本身（几乎）同意对（几乎）任何地方的个体概率的预测。我们的结论是，虽然个人的概率是不可知的，他们是通过一个计算和数据效率的过程，必须导致协议是可预测的。因此，我们不能发现自己处于这样一种情况，即我们有两个同样准确和不可改进的模型，它们的预测基本上不一致，这为有时所谓的预测或模型多重性问题提供了答案。
Individual probabilities refer to the probabilities of outcomes that are realized only once: the probability that it will rain tomorrow, the probability that Alice will die within the next 12 months, the probability that Bob will be arrested for a violent crime in the next 18 months, etc. Individual probabilities are fundamentally unknowable. Nevertheless, we show that two parties who agree on the data—or on how to sample from a data distribution—cannot agree to disagree on how to model individual probabilities. This is because any two models of individual probabilities that substantially disagree can together be used to empirically falsify and improve at least one of the two models. This can be efficiently iterated in a process of “reconciliation” that results in models that both parties agree are superior to the models they started with, and which themselves (almost) agree on the forecasts of individual probabilities (almost) everywhere. We conclude that although individual probabilities are unknowable, they are contestable via a computationally and data efficient process that must lead to agreement. Thus we cannot find ourselves in a situation in which we have two equally accurate and unimprovable models that disagree substantially in their predictions—providing an answer to what is sometimes called the predictive or model multiplicity problem.
登录
查看更多内容
影响因子：
0.6
作者：
Alvaro Sandroni
通讯作者：
Alvaro Sandroni
影响因子：
0.5
作者：
L. Bienvenu;P. Gács;M. Hoyrup;Cristobal Rojas;A. Shen
通讯作者：
A. Shen
影响因子：
0.8
作者：
R. Nau;K. McCardle
通讯作者：
K. McCardle
个人风险
DOI：
10.1111/j.1751-7176.2012.00592.x
发表时间：
2012
期刊：
The Journal of Clinical Hypertension
影响因子：
--
作者：
R. Stern
通讯作者：
R. Stern
DOI：
10.1080/01621459.1982.10477856
发表时间：
1982-09
影响因子：
3.7
作者：
A. Dawid
通讯作者：
A. Dawid