An Uncertain Regression Model

摘要：

tn this paper, we propose an uncertain regression model with an intrinsic error structure facilitated by uncertain canonical process.This model is suitable for dealing with experts knowledge ranging from small to medium size data of impreciseness.In order to have a rigorous mathematical treatments on the new regression model, we establish a series of new uncertainty concepts sequentially, soch as uncertainty joint multivariate distribution, the uncertainty distribution of uncertainty product variables, and uncertain covariance and correlation based on the axiomatic uncertainty theoretical foundation.Finally, the uncertain regression model is formulated and the estimation of the model coefficients is developed.Two examples is given for illustrating a small data regression analysis.

关键词： weighted regression model uncertain measure uncertainty variable uncertainty multivariate distribution uncertain covariance uncertain canonical process intrinsic uncertain vaiance-covariance matrix

作者: Renkuan Guo YanHong Cui Danni Guo

作者单位: Department of Statistical Sciences University of Cape Town Rondebosch 7701,Cape Town,South Africa Climate Change and Bioadapation division South African National Biodiversity Institute Kirstenbosch,

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Grey System and Intelligent Services Joint with the 15th WOSC International Congress on Cybernetics and System(2011 IEEE灰色系统与智能服务国际会议暨系统与控制世界组织第15届年会)

会议地点: 南京

会议语种:英文

页码: 173-180

在线出版日期: 2011-09-15（万方平台首次上网日期，不代表论文的发表时间）