WashU Statistics & Probability Reading Group

Probability and Statistics Reading Group
Department of Mathematics
Washington University in St. Louis

Spring 2017
Spring 2017 Information: Volunteers will present each week in one of two formats: (i) volunteers will give a brief introduction (maximum of 30 minutes) to their area of research which is accessible to non-specialists; (ii) volunteers will practice presenting a recent paper in applied statistics, such as from the list below. This is primarily intended for Ph.D. students to practice explaining their research area to a general statistics audience.

Meeting Time and Location: See schedule below. All meetings will be 2:30-3:30pm, Room 199 in Cupples I
Contact: Professor Todd Kuffner ( kuffner followed by @ followed by math dot wustl dot edu )

Schedule:

Date	Speaker	Topic
February 2	Guanshengrui Hao Ph.D. student, Dept. of Mathematics	Estimating the size of social networks slides
February 16	Min Hee Seo Ph.D. student, Dept. of Political Science	Can a synthetic panel do as well as a true panel? slides
February 23	Wei Wang Ph.D. student, Dept. of Mathematics	High-dimensional precision matrix estimation slides
March 2	Tian Wang Ph.D. student, Dept. of Mathematics	Introduction to registration problem for functional data slides
March 30	Liqun Yu Ph.D. student, Dept. of Mathematics	Divide-and-combine strategies for large-scale statistical model fitting slides Big data has imposed both opportunities and challenges for statisticians. Distributed statistical model fitting is required when the data are too big for a single computer to process and/or when data are stored in different machines. Besides subsampling methods, there are typically two approaches to large-scale statistical model fitting. One is to resort to distributed numerical algorithms that solve statistical optimization problems in parallel. And the other is to derive statistical aggregation methods that aggregate subset estimations in a way that preserves asymptotical efficiency. In this talk, I will give a brief overview of both approaches. Throughout the talk, I will be using the penalized quantile regression as a motivation example.
April 13	Luis Garcia German Ph.D. student, Dept. of Mathematics	A review of the Gaussian correlation inequality slides In 2014 Thomas Royen, a retired statistician, provided a proof of the Gaussian correlation inequality. Since then this proof has gone unnoticed up until recently when Rafal Latala (Warsaw, Poland) and one of his students called attention to it. In this talk I will discuss the history of the problem, the proof, and applications of the inequality.

Some suggested papers:

Efron, Bradley (2014). Estimation and accuracy after model selection. Journal of the American Statistical Association 109(507), 991-1007. doi:10.1080/01621459.2013.823775. http://www.tandfonline.com/doi/full/10.1080/01621459.2013.823775
De Livera, Alysha M. ; Hyndman, Rob J.; Snydera, Ralph D. (2011). Forecasting time series with complex seasonal patterns using exponential smoothing. Journal of the American Statistical Association 106(496), 1513-1527. doi:10.1198/jasa.2011.tm09771. http://www.tandfonline.com/doi/abs/10.1198/jasa.2011.tm09771
Fienberg, Stephen E. (2012). A brief history of statistical models for network analysis and open challenges. Journal of Computational and Graphical Statistics 21(4), 825-839. doi:10.1080/10618600.2012.738106. http://www.tandfonline.com/doi/abs/10.1080/10618600.2012.738106
Goel, Sharad; Rao, Justin M.; Shroff, Ravi (2016). Precinct or prejudice? Understanding racial disparities in New York City’s stop-and-frisk policy. Annals of Applied Statistics 10(1), 365--394. doi:10.1214/15-AOAS897. http://projecteuclid.org/euclid.aoas/1458909920.
Ioannidis, John P.A. (2005). Why most published research findings are false. PLoS Med 2(8): e124. doi:10.1371/journal.pmed.0020124. http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.0020124
Jaeger, Leah R.; Leek, Jeffrey T. (2014). An estimate of the science-wise false discovery rate and application to the top medical literature. Biostatistics 15 (1), 1-12. doi: 10.1093/biostatistics/kxt007. http://biostatistics.oxfordjournals.org/content/15/1/1
Li, Qunhua; Brown, James B.; Huang, Haiyan; Bickel, Peter J. (2011). Measuring reproducibility of high-throughput experiments. Annals of Applied Statistics 5(3), 1752-1779. doi:10.1214/11-AOAS466. http://projecteuclid.org/euclid.aoas/1318514284
Wong, Raymond K. W.; Kashyap, Vinay L.; Lee, Thomas C. M.; van Dyk, David A. (2016). Detecting abrupt changes in the spectra of high-energy astrophysical sources. Annals of Applied Statistics 10(2)1107-1134. doi:10.1214/16-AOAS933. http://projecteuclid.org/euclid.aoas/1469199907.

Spring 2015 Semester
Spring 2015 Information: We will focus on MCMC. Volunteers will present each week.

We will start with Chapter 1 of the Handbook of Markov Chain Monte Carlo, edited by Brooks, Gelman, Jones and Meng, published by Chapman & Hall/CRC. Some information is here.

You can find the first chapter of the Handbook here: http://www.mcmchandbook.net/HandbookChapter1.pdf

When logged in from WashU, you can access all chapters of the book through the libary by this link: http://www.crcnetbase.com/isbn/9781420079425

Professor Stanley Sawyer (emeritus professor of mathematics at WashU) authored a great set of notes available here: http://www.math.wustl.edu/~sawyer/hmhandouts/MetropHastingsEtc.pdf

Meeting Time and Location: Tuesdays, 1-2pm in Room 115 of Cupples I
Contact: Professor Todd Kuffner ( kuffner followed by @ followed by math dot wustl dot edu )

Spring 2015 Schedule:

Date	Topic/Section of Book	Discussant
02/03	HB 1.8-1.10	Han Liang Gan
02/10	HB 1.11-1.12	Guanshengrui Hao
02/17	HB 1.17	Liqun Yu
02/24	Chib, S. and E. Greenberg (1995), ``Understanding the Metropolis-Hastings Algorithm," The American Statistician, 49 (4), 327-335.	Ed Greenberg
03/03	Reversible jump MCMC; Suggested reading: HB Chapter 3, or Green and Hastie (2009), or Green (1995, Biometrika)	Tian Wang
03/17	Random Walk Metropolis-Hastings and Adaptive MCMC (time permitting); Suggested reading: HB Chapter 4 (must be logged in from WashU)	Todd Kuffner
03/24	Chan, JCC and I. Jeliazkov (2009), ``MCMC estimation of restricted covariance matrices," Journal of Computational and Graphical Statistics, 18 (2), 457-480.	Wei Wang
03/31	Convergence diagnostics for MCMC. Suggested reading: Cowles and Carlin (1996), ``Convergence diagnostics for MCMC: A Comparative Review," JASA, 91 (434), 883-904.	Michelle Torres Pacheco and Jonathan Homola
04/07	Simulated annnealing; also Gill and Casella (2004), ``Dynamic Tempered Transitions for Exploring Multimodal Posterior Distributions," Political Analysis, 12, 425-443.	Jeff Gill
04/14	Tailored randomized block Metropolis-Hastings; Chib and Ramamurthy (2010), ``Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, 155, 19-38.	Sid Chib

HB: Handbook of MCMC

Fall 2014 Semester
Fall 2014 Information: We will focus on articles of interest to the group, including both recent and classic contributions, as well as surveys. Occassionally, we may also invite a presentation from a student or outside speaker on a topic of interest. Articles will be chosen from leading journals in probability, such as:

Annals of Applied Probability
Annals of Probability
Probability Theory and Related Fields
Advances in Applied Probability
Bernoulli
Electronic Journal of Probability
Journal of Applied Probability
L'Institut Henri Poincare. Annales (B). Probabilites et Statistiques
Probability Surveys
Theory of Probability and Its Applications

Meeting Time and Location: Fridays, 12:30-1:30pm, Cupples I, Room 6

Contact: Professor Todd Kuffner ( kuffner followed by @ followed by math dot wustl dot edu )

Incentive for graduate students: Pizza, generously provided by the Department of Mathematics

Fall 2014 Schedule

Date	Paper/Topic	Discussant
19th September	Ross, Nathan F. ``Fundamentals of Stein's method." Probability Surveys, Volume 8, 2011.	Han Liang Gan
26th September	Jones, Galin L. ``On the Markov chain central limit theorem." Probability Surveys, Volume 1, 2004.	Jeff Gill
3rd October	Le Gall, Jean-Francois. ``Random trees and applications." Probability Surveys, Volume 2, 2005.	Todd Kuffner
10th October	Roberts and Rosenthal. ``Coupling and ergodicity of adaptive Markov chain Monte Carlo algorithms." Journal of Applied Probability 44 (2), 2007.	Han Liang Gan
17th October	NO MEETING (FALL BREAK)
24th October	Ramsey, F.P. ``Truth and Probability", in Ramsey, 1931, The Foundations of Mathematics and other Logical Essays, Ch. VII, p. 156-198, edited by R.B. Braithwaite, New York: Harcourt, Brace and Company.
31st October	Special Topic: The Dirichlet Process Suggested Reading: Ferguson, Thomas S. (1973). ``A Bayesian Analysis of Some Nonparametric Problems." Annals of Statistics, 1 (2), 209-230.	Jeff Gill
7th November	Two Essays of Bruno de Finetti: 1. ``Probabilism" in Erkenntnis, September 19989, 31 (2-3), p. 169-223. [Translation by Maria Concetta Di Maio, Maria Carla Galavotti and Richard C. Jeffrey of `Probabilismo', 1931.] 2. ``The logic of probability" in Philosophical Studies, 77 (1), p. 181-190, 1995. [Translation by R.B. Angell from `La logique de la probabilite", 1935.]
14th November	Robert, Christian P., Nicolas Chopin and Judith Rousseau. ``Harold Jeffreys's Theory of Probability Revisited." Statistical Science, Volume 24 (2), 141-172, 2009.