EDITORIAL: MEMORIAL ISSUE FOR CHARLES STEIN

The Institute of Mathematical Statistics (IMS) Council approved a proposal from its Committee on Memorials to dedicate this issue of the Annals of Statistics to Charles M. Stein, who died in 2016 aged 96. This memorialisation is a reflection of Stein’s distinction as a mathematical statistician, whose work continues to have a profound impact on the discipline

Exchangeable pairs, switchings, and random regular graphs

We consider the distribution of cycle counts in a random regular graph, which is closely linked to the graph's spectral properties. We broaden the asymptotic regime in which the cycle counts are known to be approximately Poisson, and we give an explicit bound in total variation distance for the approximation. Using this result, we calculate limiting distributions of linear eigenvalue functionals for random regular graphs. Previous results on the distribution of cycle counts by McKay, Wormald, and Wysocka (2004) used the method of switchings, a combinatorial technique for asymptotic enumeration. Our proof uses Stein's method of exchangeable pairs and demonstrates an interesting connection between the two techniques.Comment: Very minor changes; 23 page

Exchangeable pairs and Poisson approximation

This is a survey paper on Poisson approximation using Stein's method of exchangeable pairs. We illustrate using Poisson-binomial trials and many variations on three classical problems of combinatorial probability: the matching problem, the coupon collector's problem, and the birthday problem. While many details are new, the results are closely related to a body of work developed by Andrew Barbour, Louis Chen, Richard Arratia, Lou Gordon, Larry Goldstein, and their collaborators. Some comparison with these other approaches is offered.Comment: Published at http://dx.doi.org/10.1214/154957805100000096 in the Probability Surveys (http://www.i-journals.org/ps/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sequential importance sampling for estimating expectations over the space of perfect matchings

This paper makes three contributions to estimating the number of perfect matching in bipartite graphs. First, we prove that the popular sequential importance sampling algorithm works in polynomial time for dense bipartite graphs. More carefully, our algorithm gives a $(1-\epsilon)$-approximation for the number of perfect matchings of a $\lambda$-dense bipartite graph, using $O(n^{\frac{1-2\lambda}{8\lambda}+\epsilon^{-2}})$ samples. With size $n$ on each side and for $\frac{1}{2}>\lambda>0$, a $\lambda$-dense bipartite graph has all degrees greater than $(\lambda+\frac{1}{2})n$. Second, practical applications of the algorithm requires many calls to matching algorithms. A novel preprocessing step is provided which makes significant improvements. Third, three applications are provided. The first is for counting Latin squares, the second is a practical way of computing the greedy algorithm for a card guessing game with feedback, and the third is for stochastic block models. In all three examples, sequential importance sampling allows treating practical problems of reasonably large sizes

Eigenvalue fluctuations for random regular graphs

One of the major themes of random matrix theory is that many asymptotic properties of traditionally studied distributions of random matrices are universal. We probe the edges of universality by studying the spectral properties of random regular graphs. Specifically, we prove limit theorems for the fluctuations of linear spectral statistics of random regular graphs. We find both universal and non-universal behavior. Our most important tool is Stein's method for Poisson approximation, which we develop for use on random regular graphs. This is my Ph.D. thesis, based on joint work with Ioana Dumitriu, Elliot Paquette, and Soumik Pal. For the most part, it's a mashed up version of arXiv:1109.4094, arXiv:1112.0704, and arXiv:1203.1113, but some things in here are improved or new. In particular, Chapter 4 goes into more detail on some of the proofs than arXiv:1203.1113 and includes a new section. See Section 1.3 for more discussion on what's new and who contributed to what.Comment: 103 pages; Ph.D. thesis at the University of Washington, 201