Bayesian logistic betting strategy against probability forecasting
Bayesian logistic betting strategy against probability forecasting
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针对概率预测的贝叶斯逻辑投注策略
DOI：
10.1080/07362994.2013.741418
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发表时间：
2013
影响因子：
1.3
通讯作者：
K.
中科院分区：
文献类型：
--
作者：
Kumon;M.;Li;J.;Takemura;A. and Takeuchi;K.
在Shafer和Vovk的博弈论概率框架下，我们提出了一种基于贝叶斯逻辑回归模型的概率预测博弈的投注策略。在此策略的基础上，我们证明了带边信息的概率预测对策中强大数定律的一些结果。我们还应用我们的战略，由日本气象厅概率预测的质量进行评估。我们发现，我们的策略通过利用该机构避免明确预测的倾向而击败了该机构。
We propose a betting strategy based on Bayesian logistic regression modeling for the probability forecasting game in the framework of game-theoretic probability by Shafer and Vovk . We prove some results concerning the strong law of large numbers in the probability forecasting game with side information based on our strategy. We also apply our strategy for assessing the quality of probability forecasting by the Japan Meteorological Agency. We find that our strategy beats the agency by exploiting its tendency of avoiding clear-cut forecasts.