首页 | 本学科首页   官方微博 | 高级检索  
     检索      


A type of biased estimators for linear models with uniformly biased data
Authors:C Kotsakis
Institution:(1) Department of Geodesy and Surveying, Aristotle University of Thessaloniki, University Box 440, Thessaloniki, 54124, Greece
Abstract:The objective of this paper is the comparison of various types of estimators that can be used in linear models with uniformly biased data. This particular case refers to adjustment problems where the available measurements are affected by a common, unknown and uniform offset. The classic least-squares (LS) unbiased estimators for this type of models are reviewed in detail, and some additional remarks on their properties and performance are given. Furthermore, a family of biased estimators for linear models with uniformly biased data is introduced, which has the potential to provide better performance (in terms of mean squared estimation error) than the ordinary LS unbiased solutions. A number of different regularization viewpoints that can be equivalently associated with these biased estimators are presented, along with a discussion on various selection strategies that can be employed for the choice of the regularization parameter that enters into the biased estimation algorithm.
Keywords:Linear model  Least squares estimation  Uniformly biased data  Biased estimation  Regularization
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号