后验分布 [Posterior distribution]

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定义: 后验分布用于在贝叶斯推断中总结更新的知识，平衡先验知识与观测数据。用统计术语表述，后验分布与似然函数和先验概率的乘积成正比。后验概率分布能够反映对特定参数值的（不）确定性程度。

相关术语: Bayes Factor, Bayesian inference, Bayesian parameter estimation, Likelihood function, Prior distribution

参考文献:

  • Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5, 781. https://doi.org/10.3389/fpsyg.2014.00781
  • Lüdtke, O., Ulitzsch, E., & Robitzsch, A. (2020). A Comparison of Penalized Maximum Likelihood Estimation and Markov Chain Monte Carlo Techniques for Estimating Confirmatory Factor Analysis Models with Small Sample Sizes . https://doi.org/10.31234/osf.io/u3qag
  • van de Schoot, R., Depaoli, S., King, R., Kramer, B., Märtens, K., Tadesse, M. G., Vannucci, M., Gelman, A., Veen, D., Willemsen, J., & Yau, C. (2021). Bayesian statistics and modelling. Nature Reviews Methods Primers, 1(1), 1–26. https://doi.org/10.1038/s43586-020-00001-2

原稿作者: Alaa AlDoh

审阅者: Adam Parker, Jamie P. Cockcroft, Julia Wolska, Yu-Fang Yang, Charlotte R. Pennington

翻译者: AI-driven translation tool "TransFlow" (developed by Jinbiao Yang and COSN OpenTransfer team)

译稿审阅者: Zixi Wang, Liangjie Chen, Ruoting Liu, Shuxian Jin