Workshop on sequential Monte Carlo methods: filtering and other applications, 3-5 July 2006 St Anne's College Oxford

本提案的目的是资助一个关于顺序蒙特卡罗方法及其各种应用的研讨会，如滤波和贝叶斯推理，大约40名研究人员和研究生将于2006年7月3日至5日在牛津大学圣安妮学院举行。这是致力于该领域的一系列成功的跨学科研讨会的第四版，该研讨会于1999年12月在剑桥开始，并于2000年7月和2004年7月分别在牛津和巴塞罗那举行了两次进一步的研讨会。本次研讨会由Dr. Christophe Andrieu （Bristol）和Dr. Dan Crisan （Imperial）组织。当地的组织者是特里·莱昂斯教授，他是牛津大学圣安妮学院的研究员。序列蒙特卡罗方法是非常重要的统计数值技术，在过去的15年里，它彻底改变了统计滤波（一个专门用于估计部分观察到的动态过程的统计/概率领域，有许多实际应用），并对信号处理（例如目标跟踪）计算机科学（例如计算机视觉，机器人技术），以及金融统计，计量经济学和生物统计学产生了深远的影响。该方法现在发展得相当好，并且出现了一种关于这些过程的理论，该理论在一定程度上支持该方法。然而，在方法和理论层面上仍然存在许多悬而未决的问题：例如，尚未找到一种令人满意的技术来解决静态参数估计的全部一般性问题，而在理论层面上，只能在相当严格的技术条件下证明该方法的准确性和稳定性，而这些条件在实践中很少得到满足。

The aim of this proposal is to fund a Workshop on sequential Monte Carlo methods and their various applications, such as filtering and Bayesian inference, of about 40 researchers and postgraduate students to be held at St Anne's College Oxford, 3-5 July 2006. This is meant to be the fourth edition of a successful series of interdisciplinary workshops dedicated to the area, which started in December 1999 in Cambridge, and has been followed in July 2000 and July 2004 by two further editions, in Oxford and Barcelona respectively. The present workshop is organised by Dr. Christophe Andrieu (Bristol) and Dr. Dan Crisan (Imperial). The local organiser is Prof. Terry Lyons, who is a fellow of St Anne's college, Oxford. Sequential Monte Carlo methods are very important statistical numerical techniques that have revolutionised statistical filtering (an area of statistics/probability dedicated to the estimation of partially observed dynamic processes, which has many practical applications) over the last 15 years and have had a profound impact in signal processing (e.g. target tracking) computer science (e.g. computer vision, robotics), but also financial statistics, econometrics and biostatistics. The methodology is now rather well developed and a theory of such processes has emerged that partly supports the methodology. However many open questions still remain, both at a methodological and theoretical level: for example, a satisfactory technique to address the problem of static parameter estimation in its full generality is yet to be found, while at a theoretical level, accuracy and stability of the method can only be proved under rather restrictive technical conditions which are only rarely met in practice.