贝叶斯数据分析
Bayesian data analysis
Andrew Gelman、John B. Carlin、Hal S. Stern、Donald B. Rubin · 初版 1995 年
27人推荐
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为什么值得读
- 包含真实数据集的实践案例研究
- 展现结合多种指标与质性检验的方法
- 系统了解贝叶斯统计与计算的优秀读物
“《Bayesian Data Analysis》从贝叶斯视角全面阐述了数据的统计分析。本书着重介绍了现代计算工具，推断通常借助计算机模拟来实现。”“书中阐明了贝叶斯分析的各项原理，重在实用而非理论推导，并结合实际数据进行了生动演示。书中探讨了多种模型，包括线性回归、分层（随机效应）模型、稳健模型、广义线性模型以及混合模型。”“本书两个重要且独特的特色在于……”
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……假期，学点新东西，不一定非得跟工作相关。不过今年我还没想好该翻哪本书。很想看看你们的夏季阅读书单都有啥。我最近的最爱：《Bayesian Data Analysis》（第3版），Gelman 等人著；《Designing Data-Intensive Applications》，Martin Kleppmann 著；《The Art of Electronics》，Horowitz & Hill 著
…vacation, to learn something new and not necessarily work-related. This year, however, I am not sure which book to pick up. I would love to see what's on your summer reading lists. My recent favourites: Bayesian Data Analysis, 3rd ed, by Gelman et al Designing Data-Intensive Applications, by Martin Kleppmann The Art of Electronics, by Horowitz & Hill
……该领域写得极好的书。另一本历久弥新的老书是 E. T. Jaynes 的《Probability Theory: the Logic of Science》。Tibshirani 的《Elements of Statistical Learning》也很棒。Andrew Gelman 的《Bayesian Data Analysis》是另一本大作。Ian Goodfellow 和 Yoshua Bengio 的《Deep Learning》很适合用来跟进该领域的最新进展。
…written books in the field. Another old book that stands up very well is "Probability Theory: the Logic of Science" by E. T. Jaynes. "Elements of Statistical Learning" by Tibshirani is also good. "Bayesian Data Analysis" by Andrew Gelman is another great read. "Deep Learning" by Ian Goodfellow and Yoshua Bengio is useful for getting caught up with recent advances in that field.
……起步的地方是：3.) Lehmann, E. (2004). 《Elements of Large-Sample Theory》Springer。那些全是频率学派的书。你还应该读点贝叶斯学派的：4.) Gelman, A. 等 (2003). 《Bayesian Data Analysis》Chapman & Hall/CRC。而且你应该开始了解贝叶斯计算：5.) Robert, C. 和 Casella, G. (2005). 《Monte Carlo Statistical Methods》Springer。概率论方面，一个……
…starting place is: 3.) Lehmann, E. (2004). "Elements of Large-Sample Theory" Springer. Those are all frequentist books. You should also read something Bayesian: 4.) Gelman, A. et al. (2003). "Bayesian Data Analysis" Chapman & Hall/CRC. and you should start to read about Bayesian computation: 5.) Robert, C. and Casella, G. (2005). "Monte Carlo Statistical Methods" Springer. On the probability front, a…
……E. T. Jaynes 的《Logic of Science》http://www.med.mcgill.ca/epidemiology/hanley/bios601/Gaussia... Tibshirani 的《Elements of Statistical Learning》https://web.stanford.edu/~hastie/Papers/ESLII.pdf Andrew Gelman 的《Bayesian Data Analysis》http://hbanaszak.mjr.uw.edu.pl/TempTxt/(Chapman%20&%20Hall_C...
…Logic of Science" by E. T. Jaynes http://www.med.mcgill.ca/epidemiology/hanley/bios601/Gaussia... "Elements of Statistical Learning" by Tibshirani https://web.stanford.edu/~hastie/Papers/ESLII.pdf "Bayesian Data Analysis" by Andrew Gelman http://hbanaszak.mjr.uw.edu.pl/TempTxt/(Chapman%20&%20Hall_C...
……我觉得要有帮助的话，你必须给出复现研究的案例，但不能只做指标优化，而是换成全方位的多维度指标加上定性核验。如果你想读到用真实数据集进行这种实操的优秀范例，我推荐 Gelman 等人的《Bayesian Data Analysis》以及 Gelman 和 Hill 的《Data Analysis Using Regression and Multilevel/Hierarchical Models》。确实存在……
…think to be helpful you have to present case studies of reproducing research but with metric optimization swapped out for a holistic variety of metrics plus qualitative checking. I recommend the books Bayesian Data Analysis by Gelman et al and Data Analysis Using Regression and Multilevel/Hierarchical Models by Gelman and Hill if you want to read good accounts of doing this in practice with real data sets. There’s definitely…
你可以去读 Gilbert Strang 的线性代数书，网上也有视频课……Gelman 的《Bayesian Data Analysis》是一本偏贝叶斯视角的优秀统计学入门书，可能还有 Freedman 的《Statistical Models》，再读本通用的机器学习入门书，比如 Alpaydin 的，或者想看更多概率视角的就选 Bishop。至于 NLP……
You could read Gilbert Strang's Linear Algebra books, there are also video lectures available... Gelman's Bayesian Data Analysis is a good statistical intro with a Bayesian bend, maybe Freedman's Statistical models, read some general machine learning intro book, such as Alpaydin or Bishop for a more probabilistic view. For NLP…