首页 / COURSES / 数理统计实验班 MATHEMATICAL STATISTICS (HONORS) - TA / 课程资料 /

Readings

Books

  1. An Introduction to Mathematical Statistics by Fetsje Bijma, Marianne Jonker, and Aad van der Vaart (2017). https://doi.org/10.5117/9789462985100
  2. All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman (2004). https://doi.org/10.1007/978-0-387-21736-9, Course taught by the same author: https://www.stat.cmu.edu/~larry/=stat705
  3. Fisher, Neyman, and the Creation of Classical Statistics by Erich L. Lehmann (2011). https://doi.org/10.1007/978-1-4419-9500-1
  4. Probability and Statistics for Economists by Bruce E. Hansen (2022). https://www.ssc.wisc.edu/~bhansen/probability
  5. Elements of Distribution Theory by Thomas A. Severini (2005). https://doi.org/10.1017/CBO9780511610547
  6. Mathematical Statistics (Second Edition) by Jun Shao (2003). https://doi.org/10.1007/b97553, Courses taught by the same author: https://pages.stat.wisc.edu/~shao/stat709/main.html, https://pages.stat.wisc.edu/~shao/stat710/main.html
  7. Theoretical Statistics: Topics for a Core Course by Robert W. Keener (2010). https://doi.org/10.1007/978-0-387-93839-4
  8. From Finite Sample to Asymptotic Methods in Statistics by Pranab K. Sen, Julio M. Singer, and Antonio C. Pedroso de Lima (2009). https://doi.org/10.1017/CBO9780511806957
  9. A Course in Mathematical Statistics and Large Sample Theory by Rabi Bhattacharya, Lizhen Lin, and Victor Patrangenaru (2016). https://doi.org/10.1007/978-1-4939-4032-5
  10. A Course in Large Sample Theory by Thomas S. Ferguson (1996). https://doi.org/10.1201/9781315136288, Course taught by the same author: https://www.math.ucla.edu/~tom/Stat200C.html
  11. Asymptotic Statistics by A. W. van der Vaart (1998). https://doi.org/10.1017/CBO9780511802256, Excerpt Notes (Mathematische Statistiek) by the same author: https://staff.fnwi.uva.nl/p.j.c.spreij/onderwijs/TI/AsympStat-LecNotes2010.pdf
  12. Nonparametric Statistical Methods (Third Edition) by Myles Hollander, Douglas A. Wolfe, and Eric Chicken (2014). https://doi.org/10.1002/9781119196037
  13. Introduction to Nonparametric Estimation by Alexandre B. Tsybakov (2009). https://doi.org/10.1007/b13794
  14. The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Second Edition) by Christian P. Robert (2007). https://doi.org/10.1007/0-387-71599-1
  15. The frequentist theory of Bayesian statistics by B. J. K. Kleijn (expected 2022). https://staff.fnwi.uva.nl/b.j.k.kleijn/Research.html

Notes

  1. Exponential Families in Theory and Practice by Bradley Efron. https://www.cs.columbia.edu/~blei/fogm/2018F/materials/Efron2018.pdf
  2. Advanced Mathematical Statistics by Bing-Yi Jing‬. http://www.mathstat.org/forum.php?mod=viewthread&tid=4716
  3. Fundamentals of Mathematical Statistics by Sara van de Geer. https://stat.ethz.ch/lectures/as20/mathstat.php#course_materials
  4. Asymptotics for Statisticians by David R. Hunter. http://personal.psu.edu/drh20/asymp/lectures
  5. Asymptotic Statistics by Changliang Zou. http://web.stat.nankai.edu.cn/chlzou/Note_AS.pdf
  6. Nonparametric Statistics by Eduardo García Portugués. https://bookdown.org/egarpor/NP-UC3M
  7. Introduction to Nonparametric Statistics by Bodhisattva Sen. https://stat.columbia.edu/~bodhi/Talks/Intro&NP-Stat.pdf

Articles

  1. Philosophy of Statistics by Jan-Willem Romeijn (2014). https://plato.stanford.edu/entries/statistics
  2. Statistical Inference: The Big Picture by Robert E. Kass (2011). https://doi.org/10.1214/10-STS337
  3. Model Specification: The Views of Fisher and Neyman, and Later Developments by E. L. Lehmann (1990). https://doi.org/10.1214/ss/1177012164
  4. Role of Models in Statistical Analysis by D. R. Cox (1990). https://doi.org/10.1214/ss/1177012165
  5. What is a statistical model? by Peter McCullagh (2002 AoS). https://doi.org/10.1214/aos/1035844977
  6. Univariate Distribution Relationships by Lawrence M. Leemis and Jacquelyn T. McQueston (2008). https://doi.org/10.1198/000313008X270448, http://www.math.wm.edu/~leemis/chart/UDR/UDR.html
  7. A Note on Bivariate Distributions That are Conditionally Normal by Andrew Gelman and Xiao-Li Meng (1991). https://doi.org/10.1080/00031305.1991.10475784
  8. A tale of two countries: The Craig–Sakamoto–Matusita theorem by Junjiro Ogawa and Ingram Olkinab (2008). https://doi.org/10.1016/j.jspi.2005.09.010
  9. A Sufficiency Paradox: An Insufficient Statistic Preserving the Fisher Information by Abram Kagan and Lawrence A. Shepp (2005). https://doi.org/10.1198/000313005X21041
  10. An Interpretation of Completeness and Basu's Theorem by E. L. Lehmann (1981 JASA). https://doi.org/10.1080/01621459.1981.10477652
  11. An Essay on Statistical Decision Theory by Lawrence D. Brown (2000 JASA). https://doi.org/10.1080/01621459.2000.10474329
  12. C. Radhakrishna Rao: A Century in Statistical Science by Nandini Kannan and Debasis Kundu (2021). https://doi.org/10.1111/insr.12467, https://cosx.org/2021/08/a-century-in-statistical-science
  13. Applications of the van Trees Inequality: A Bayesian Cramér-Rao Bound by Richard D. Gill and Boris Y. Levit (1995 Bernoulli). https://doi.org/10.2307/3318681
  14. Maximum Likelihood: An Introduction by L. Le Cam (1990). https://doi.org/10.2307/1403464
  15. The Epic Story of Maximum Likelihood by Stephen M. Stigler (2007). https://doi.org/10.1214/07-STS249
  16. The Interplay of Bayesian and Frequentist Analysis by M. J. Bayarri and J. O. Berger (2004). https://doi.org/10.1214/088342304000000116
  17. Philosophy and the practice of Bayesian statistics by Andrew Gelman and Cosma Rohilla Shalizi (2013). https://doi.org/10.1111/j.2044-8317.2011.02037.x
  18. Why Isn't Everyone a Bayesian? by B. Efron (1986). https://doi.org/10.1080/00031305.1986.10475342
  19. Objections to Bayesian statistics by Andrew Gelman (2008). https://doi.org/10.1214/08-BA318
  20. Bayes, Oracle Bayes and Empirical Bayes by Bradley Efron (2019). https://doi.org/10.1214/18-STS674, https://efron.ckirby.su.domains/talks/2017Bayes-OBayes-EBayes.pdf
  21. Could Fisher, Jeffreys and Neyman Have Agreed on Testing? by James O. Berger (2003). https://doi.org/10.1214/ss/1056397485
  22. P Values: What They Are and What They Are Not by Mark J. Schervish (1996). https://doi.org/10.2307/2684655
  23. Why are p-Values Controversial? by Todd A. Kuffner and Stephen G. Walker (2019). https://doi.org/10.1080/00031305.2016.1277161
  24. From Statistically Significant to Significantly Statistical by Xiao-Li Meng (2019). https://imstat.org/2019/05/15/presidents-column-statistical-significance, https://cosx.org/2019/08/significantly-statistical
  25. Bayes Factors by Robert E. Kass and Adrian E. Raftery (1995 JASA). https://doi.org/10.1080/01621459.1995.10476572
  26. Demystify Lindley's Paradox by Interpreting P-value as Posterior Probability by Guosheng Yin and Haolun Shi (2020). https://arxiv.org/abs/2002.10883
  27. The Emperor’s new tests by Michael D. Perlman and Lang Wu (1999). https://doi.org/10.1214/ss/1009212517
  28. The Mean Value Theorem and Taylor’s Expansion in Statistics by Changyong Feng, Hongyue Wang, Yu Han, Yinglin Xia, and Xin M. Tu (2013). https://doi.org/10.1080/00031305.2013.844203
  29. The Likelihood Ratio, Wald, and Lagrange Multiplier Tests: An Expository Note by A. Buse (1982). https://doi.org/10.2307/2683166
  30. Superefficiency from the Vantage Point of Computability by Vladimir Vovk (2009). https://doi.org/10.1214/09-STS279
  31. Integrated Square Error Properties of Kernel Estimators of Regression Functions by Peter Hall (1984 AoS). https://doi.org/10.1214/aos/1176346404
  32. Concentration Inequalities for Statistical Inference by Huiming Zhang and Song Xi Chen (2021). https://arxiv.org/abs/2011.02258
  33. What are the Most Important Statistical Ideas of the Past 50 Years? by Andrew Gelman and Aki Vehtari (2021 JASA). https://doi.org/10.1080/01621459.2021.1938081
  34. Citations for the IMS Bulletin Article on 215 Influential Ideas and Discoveries in Statistics, 1650 − 2010 by Anirban DasGupta (2013). https://www.stat.purdue.edu/~dasgupta/discoveries.pdf
  35. Reading the Classics by Anirban DasGupta. https://www.stat.purdue.edu/~dasgupta/bulletincolumn-1.pdf
  36. Selected Works of E. L. Lehmann. https://doi.org/10.1007/978-1-4614-1412-4

    Applications

    课程: 

    数理统计实验班 Mathematical Statistics (Honors) - TA