桂林理工大学学报2013，Vol.33Issue(2)：297-301,5.DOI:10.3969/j.issn.1674-9057.2013.02.017
半参数模型补偿最小二乘平滑参数求解新方法
New Method to Acquire Smoothing Parameter of Semi-Parametric Model Under Penalized Least Squares
摘要
Abstract
The semi-parametric model under the penalized least squares method for survey adjustment is based on the principle of balance between the weighted sum-squared residual errors and systematic errors.This balance is achieved by attaching a smoothing parameter to the penalized part.That is systematic errors part.Because large selecting scale of the smoothing parameter,selecting an appropriate smoothing parameter becomes a difficult and key problem.A method of semi-parametric model under the penalized least squares with weight scaling factor is put forward and the formula and statistical properties of estimates are deduced.To ensure the balance of the two parts,the sum of weight scaling factors of two parts must be equal to 1 and restricted between 0 and 1,greatly reduces the smoothing parameter selection range.The simulated examples are demonstrated and some conclusions are drawn.关键词
半参数模型/补偿最小二乘/平滑参数/相对权比Key words
semi-parametric model/ penalized least squares/ smoothing parameters/ weight scaling factor分类
天文与地球科学引用本文复制引用
张俊,文鸿雁,张显云..半参数模型补偿最小二乘平滑参数求解新方法[J].桂林理工大学学报,2013,33(2):297-301,5.基金项目
国家自然科学基金项目(41071294) （41071294）
贵州省自然科学基金项目(黔科合J字[2009] 2264) （黔科合J字[2009] 2264）
广西空间信息与测绘重点实验室资助课题(桂科能1103108-02) （桂科能1103108-02）
贵州大学青年自然科学基金项目(贵大自青基合字2009 (077)) （贵大自青基合字2009 (077）
