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Progress in Stein's Method
(5 January - 6 February 2009)

... Jointly organized with Department of Mathematics and Department of Statistics and Applied Probability in celebration of 80th Anniversary of Faculty of Science


Organizing Committee · Visitors and Participants · Overview · Activities · Funding for Young Scientists


 Organizing Committee



  • Andrew Barbour (University of Zurich)



  • Louis Chen (National University of Singapore)
  • Kwok Pui Choi (National University of Singapore)


 Visitors and Participants





One of the greatest achievements of probability has been its success in approximating the distributions of arbitrarily complicated random processes in terms of a rather small number of ‘universal’ processes — Brownian motion, the Poisson process, the Ewens sampling formula, Airy processes, stochastic Loewner evolution and so on. The standard approach is to consider sequences of processes, indexed by a parameter n, and to establish that suitably normalized versions of the processes converge in distribution to one of the standard processes as n tends to infinity. However, for practical purposes, it is much more important to know how accurate such an approximation is for a particular process with a fixed value of n, and this is a more difficult question to answer. For instance, central limit theorems were known already around 1715, and in full generality by 1900, whereas the corresponding approximation theorem of Berry and Esseen was only proved in 1941. Stein’s method, introduced in 1970, offers a general means of solving such problems. By constructing and exploiting a novel characteristic operator associated with a random system — most often, the one used as the approximation — it turns out to be possible to make precise assessments of the approximation error in a wide variety of circumstances.

Stein’s original application was in the context of central limit approximation to partial sums of random variables having a stationary dependence structure, a problem involving the normal distribution and the real line. However, his method has a big advantage over most other techniques in that it can in principle be used for approximation in terms of any distribution on any space, including random variables on the real line, processes on a space of sequences, functions or measures, and combinatorial structures on discrete spaces. A further big advantage over its competitors is that strong independence requirements are not needed to make the method work (though they may of course simplify many arguments and the form of the bounds that can be attained). As a result of this considerable freedom, its uses have proliferated, with approximations not only to the normal distribution, but also to the Poisson distribution, to multivariate normal distributions, to diffusions, to Poisson processes, to the Ewens sampling formula, to the Wigner semi-circle law, and more. The proceedings of a workshop in the program ‘Stein’s method and applications: a program in honor of Charles Stein’, held at the Institute for Mathematical Sciences of the National University of Singapore in August 2003, illustrate the variety and richness of the field.

In the five years since that program was held, and stimulated to a considerable degree by the impulse that it provided, there have been a number of significant new developments. The first of these concerns large deviations and concentration inequalities. A second new field is the application of Stein’s method to problems having an essentially algebraic component. A third area is the combination of Stein's method with Malliavin calculus to prove bounds in normal and gamma approximation of functionals of infinite-dimensional Gaussian fields. A fourth area in which the method is finding increasing application is that of random geometrical graphs. All these new developments have opened up new ways to a wider range of applications of Stein’s method.

In view of the breadth and diversity of these and other recent advances, the time is now ripe to hold a further program, with the aim of bringing together the people actively involved in the area, and of cementing and further promoting the development of the field. In addition to the general scientific aim, program is also designed to develop research in Stein’s method in Southeast Asia, where there is a growing interest in the method. It also aims, by way of a series of tutorial lectures, to encourage more young mathematicians to undertake research in the field.




  • Tutorials

    5 - 9 Jan 2009

    (a) Poisson approximation, by Andrew Barbour
    (b) Normal approximation, by Larry Goldstein
    (c) Malliavin calculus and related topics, by Giovanni Peccati
    (d) Applications in algebra, by Jason Fulman

    22 - 23 Jan 2009

    (e) Stein's method in concentration inequalities, spin glasses, random matrices, and strong approximations, by      Sourav Chatterjee

  • Workshop

    12 - 16 Jan 2009

  • Graduate Seminar

    19 - 20 Jan 2009

  • Informal Minisymposium

    Date: 28 Jan 2009
    Time: 10:00am
    Venue: IMS Seminar Room (House 3)


Students and researchers who are interested in attending these activities and who do not require financial aid are requested to complete the online registration form.

The following do not need to register:

  • Those invited to participate.
  • Those applying for financial support.





 Funding for Young Scientists


The Institute for Mathematical Sciences invites applications for membership for participation in the above program. Limited funds to cover travel and living expenses are available to young scientists. Applications should be received at least three (3) months before the commencement of membership. Application form is available in (MSWord|PDF|PS) format for download.


More information is available by writing to:
Institute for Mathematical Sciences
National University of Singapore
3 Prince George's Park
Singapore 118402
Republic of Singapore

or email to imssec(AT)



Organizing Committee · Visitors and Participants · Overview · Activities · Funding for Young Scientists

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