Mathematical Sciences: Workshop on Statistical Mixture Modelling

建议：DMS 94-24490 PI：迈克韦斯特标题：车间统计混合建模摘要：研讨会提供了一个论坛，以回顾和宣传广泛分散的混合建模研究活动，促进理论，方法和计算研究方向在不久的将来的施肥，并且重要的是，将注意力集中在复杂随机系统中应用问题的新兴领域，这些系统本质上是以混合术语结构的。讲习班将主要集中于具有强跨学科和计算成分的专题问题，包括密度估计、回归和时间序列等领域的混合问题；混合统计图像建模和分析，神经网络和信号处理；图形模型和网络；混合分析的随机模拟；聚类与分类问题；模型选择与组合；混合推理的替代方法；潜在变量和不完整数据问题；以及混合物在不同科学领域的应用。举办讲习班是为了认识到最近在理论方面的增长和发展，特别是基于混合分布的统计方法的应用。混合模型在科学、工程和社会科学中许多复杂的建模和推理问题中起着关键作用，计算统计技术的进步已经并将继续促进混合模型的广泛应用。本次研讨会提供了一个论坛，回顾和宣传广泛分散的混合建模研究活动，促进理论，方法和计算研究方向在不久的将来的施肥，并将注意力集中在混合条件固有结构的复杂随机系统中的各种重要应用问题上。研讨会将汇集来自不同背景的资深研究人员、新研究人员和学生，在统计混合建模的前沿进行交流和互动，以突出统计技术在这些领域的发展，促进不同应用领域研究人员之间的交流，并突出混合模型在遗传学、天文学和物理学、神经科学等不同领域的实用性。

PROPOSAL: DMS 94-24490 PI: Mike West TITLE: WORKSHOP ON STATISTICAL MIXTURE MODELLING ABSTRACT: The Workshop provides a forum for reviewing and publicizing widely dispersed research activities in mixture modelling, to stimulate fertilization of theoretical, methodological and computational research directions for the near future, and, significantly, to focus attention on the burgeoning arena of applied problems in complex stochastic systems that are inherently structured in mixture terms. The Workshop will heavily concentrate in topical problems with strong cross-disciplinary and computational components, featuring mixture problems in areas such as density estimation, regression and time series; mixtures in statistical image modelling and analysis, neural networks and signal processing; graphical models and networks; stochastic simulation for mixture analysis; clustering and classification problems; model selection and combination; alternative approaches to inference in mixtures; latent variables and incomplete data problems; and applications of mixtures in various scientific areas. The Workshop is held in recognition of the recent growth and development in the theory and, in particular, applications of statistical methods based on mixtures of distributions. Mixture models play key roles in many complex modelling and inference problems in science, engineering and social sciences, and advances in computational statistical technology have, and continue to, promote their wider use. This Workshop provides a forum for reviewing and publicizing widely dispersed research activities in mixture modelling, stimulating fertilization of theoretical, methodological and computational research directions for the near future, and focusing attention on the wide variety of significant applied problems in complex stochastic systems that are inherently structured in mixture terms. The workshop will bring together senior researchers, new researchers and students from various backgrounds to prom ote exchange and interactions on the frontiers of statistical mixture modelling, to highlight the development of statistical technology across these fields, to promote interchanges between researchers in various applied fields, and to highlight the utility of mixture models in diverse fields such as genetics, astronomy and physics, the neuro-sciences, and others.