Generalized Linear Mixed Models-book.pdf

The original purpose of the book was to present a unified theoretical and conceptual framework for statistical modelling in a way that was accessible to undergraduate students and researchers in other fields. The second edition was expanded to include nominal and ordinal logistic regression, survival analysis and analysis of longitudinal and clustered data. It relied more on numerical methods, visualizing numerical optimization and graphical methods for exploratory data analysis and checking model fit. The third edition added three chapters on Bayesian analysis for general- ized linear models. To help with the practical application of generalized linear models, Stata, R and WinBUGS code were added. This fourth edition includes new sections on the common problems of model selection and non-linear associations. Non-linear associations have a long history in statistics as the first application of the least squares method was when Gauss correctly predicted the non-linear orbit of an asteroid in 1801. Statistical methods are essential for many fields of research, but a widespread lack of knowledge of their correct application is creating inaccu- rate results. Untrustworthy results undermine the scientific process of using data to make inferences and inform decisions. There are established practices for creating reproducible results which are covered in a new Postface to this edition.

作者：Vidal, René, Ma, Yi, Sastry, S.S. 2016年新书。据作者说：研究 unsupervised learning，从一百多年前的PCA讲到压缩感知，知识纵跨上百年。横跨代数几何，数理统计，高维数据处理，优化算法。而应用更涉及科学和工程各个领域，是数据科学的入门基础

机器人广义逆的理论与应用

广义主成因分析，马毅教授的代表作，原版pdf，非影印版。

Hastie的成名作，扩展的加性模型，从统计角度看待Adaboost。成书于1990年。 Hastie. Generalized Additive Models, Chapman and Hall, 1990.

针对Generalized Benders Decomposition原始论文逐步进行推导，直到推导出Generalized Benders Decomposition的一般解法

应用广泛的广义相加模型，可以进行时间序列分析（如环境污染物与健康的关系）。