P-NORM SEMIPARAMETRIC REGRESSION MODEL

摘要：

In this paper, using the kernel weight function, we obtain the parameter estimation of p-norm distribution in semi-parametric regression model, which is effective to decide the distribution of random errors.Under the assumption that the distribution of observations is unimodal and symmetry, this method can give the estimates of the parameters.Finally, two simulated adjustment problem are constructed to explain this method.The new method presented in this paper shows an effective way of solving the problem.The estimated values are nearer to their theoretical ones than those by least squares adjustment approach.

关键词： P-norm distributions Semi-parametric regression Kernel weight function Maximum likelihood adjustment

作者: PAN XIONG

作者单位: Faculty of Engineering, China University of Geosciences, 388 Lumo Road, Wuhan, 430074, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 2461-2466

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）