數統電腦自學資源:
A. Maths:
Linear algebra:
ODE:
PDE:
Numerical analysis:
Optimisation: Boyd, S. & Vandenberghe, L. (2004). Convex Optimization. Cambridge University Press. URL
https://www.stanford.edu/~boyd/cvxbook/
Elementary probability: Ross, S. M. (2014). A First Course in Probability (9th edition). Pearson.
Measure-theoretic probability theory: Chung, K. L. (2000). A Course in Probability Theory (2nd edition). Academic Press.
Elementary stochastic processes: Ross, S. M. (2014). Introduction to Probability Models (11th edition). Academic Press.
Stochastic calculus: Øksendal, B. (2003). Stochastic Differential Equations (6th edition). Universitext. Springer, Berlin, Heidelberg.
B. Statistics:
Elementary statistics: Miller, I., Miller, M., & Freund, J. E. (1999). John E. Freund's mathematical statistics. Prentice Hall. (easier)
Hogg, R. V., & Craig, A. T. (1995). Introduction to mathematical statistics.(5"" edition) (pp. 269-278). Upper Saddle River, New Jersey: Prentice Hall. (more difficult)
Linear models: Neter, J., Kutner, M. H., Nachtsheim, C. J., & Wasserman, W. (1996). Applied Linear Statistical Models (Vol. 4). Chicago: Irwin.
Bayesian inference: Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2014). Bayesian Data Analysis (Vol. 2). Boca Raton, FL: CRC press.
Generalized Linear Model: Myers, R. H., Montgomery, D. C., Vining G. G., Robinson T. J. (2010). Generalized Linear Models: with Applications in Engineering and the Sciences (2nd Edition). Wiley.
Multilevel/mixed models: Gelman, A., & Hill, J. (2014). Data analysis using regression and multilevel hierarchical models (Vol. 1). New York, NY, USA: Cambridge University Press.
Multivariate:
Study design: Montgomery, D. C. (2017). Design and analysis of experiments. John wiley & sons.
Time series: Tsay, R. S. (2010). Analysis of Financial Time Series (3rd edition). Wiley.
Categorical data analysis: Agresti, A. (2007). An Introduction to Categorical Data Analysis (2nd Edition), Wiley Series in Probability and Statistics. Wiley.
Bootstrap: Efron, B. & Tibshirani, R. (1994). An Introduction to the Bootstrap. Chapman and Hall/CRC.
Statistical inference: Casella, G. & Berger, R. L. (2001). Statistical Inference (2nd Edition). Duxbury Press.
Statistical learning: Hastie, T., Tibshirani, R. & Friedman J. (2016). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd Edition), Springer Series in Statistics. Springer.
C. Computer Science:
Basic programming:
Information retrieval:
Computational phylogenetics:
Machine learning: Bishop, C. M. (2011). Pattern Recognition and Machine Learning. Springer.
Deep learning: Goodfellow, I., Bengio, Y. & Courville, A. (2016). Deep Learning. The MIT Press.
精選papers:
Phy :
https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.87.981
http://phys.sinica.edu.tw/~nano/article/e-04.pdf
Maths:
http://jstor.org/stable/1969529?seq=1#page_scan_tab_contents
http://ncbi.nlm.nih.gov/pmc/articles/PMC1063129
http://arxiv.org/abs/1704.07210
Econ:
http://researchgate.net/profile/Ariel_Rubinstein2/publication/4719889_The_Electronic_Mail_Game_Strategic_Behavior_Under_Almost_Common_Knowledge/links/004635309c7e0b6a58000000.pdf
CS/EE:
http://statweb.stanford.edu/~candes/papers/StableRecovery.pdf
http://math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf
Bio:
http://nature.com/nbt/journal/v34/n1/full/nbt.3439.html?foxtrotcallback=true
Psychology:
http://journals.sagepub.com/doi/abs/10.1177/0956797611417632
http://cambridge.org/core/journals/behavioral-and-brain-sciences/article/weirdest-people-in-the-world/BF84F7517D56AFF7B7EB58411A554C17
http://nature.com/articles/s41562-017-0189-z
https://www.nature.com/polopoly_fs/1.16275!/menu/main/topColumns/topLeftColumn/pdf/515009a.pdf
Arts and humanities:
https://www.sciencedirect.com/science/article/pii/S0749596X07001398
歡迎大家繼續擴充
LIHKG Research Post FAQ正式上線了 
