International Workshop on Wavelets in Statistics; October 12-13, 1997; Durham, NC

DMS 9700733统计小波国际研讨会，杜克大学，美国北卡罗来纳州达勒姆。1997年10月12日至13日。布拉尼·维达科维奇摘要。近年来，统计小波建模和计算研究已经成为理论统计和应用统计学的新兴领域，并开始影响统计方法论和各个应用科学领域的发展。小波思想在回归、密度和函数估计、因子分析、时间序列分析中的建模和预测、空间统计等统计学领域得到了发展，并在科学和工程中得到了广泛的应用。对贝叶斯统计建模和小波的新兴趣正在为两个研究领域的接口产生令人兴奋的新方向，对未来的应用工作具有重大影响。这一国际研究研讨会的重点是小波和统计科学的接口，是为了承认最近在各学科接口的研究的增长和当前的活力。会议将提供一个机会，总结统计中小波研究的现状，探讨统计中子波建模和小波在统计学中的应用影响，并提出和鼓励新的理论、方法和计算研究方向。计划在适当的时候举办讲习班，以评估和解决未来前景的双重问题：小波思想对统计科学和应用的重大贡献，以及通过使用统计概念和模型进一步发展基于小波的技术。

DMS 9700733 INTERNATIONAL WORKSHOP ON WAVELETS IN STATISTICS ISDS, Duke University, Durham, NC, USA. October 12-13, 1997. Brani Vidakovic Abstract. Statistical wavelet modeling and computational research have, in recent years, become burgeoning areas in both theoretical and applied statistics, and are beginning to impact developments in statistical methodology and in various applied scientific fields. Wavelet ideas are developing in statistics in areas such as regression, density and function estimation, factor analysis, modeling and forecasting in time series analysis, spatial statistics, with ranges of application areas in science and engineering. The emerging interests in Bayesian statistical modeling and wavelets is generating exciting new directions for the interface of two research areas, with significant potential for future impact on applied work. This international research workshop, focused on the interface of wavelets and statistical science, is held in recognition of the recent growth and current vibrancy of research at the interface of the disciplines. The meeting will provide an opportunity to summarize the current status of research on wavelets in statistics, to explore the applied impact that statistical wavelet modeling and wavelet in statistics are having, and to suggest and stimulate novel theoretical, methodological and computational research directions. The workshop is planned at an opportune time to assess and address the dual question of the future prospects: for significant contributions of wavelet ideas to statistical science and application, and for furthering watelet-based technology through the use of statistical concepts and models.