Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/2307
Title: Best linear near unbiased estimation for nonlinear signal models via semi-infinite programming approach
Author(s): Siu, Wan Chi 
Author(s): Ling, B. W.-K.
Ho, C. Y.-F.
Dai, Q.
Issue Date: 2015
Publisher: Elsevier
Journal: Computational Statistics & Data Analysis 
Volume: 88
Start page: 111
End page: 118
Abstract: 
When the exact unbiasedness condition is relaxed to a near unbiasedness condition, this short communication shows that the best linear near unbiased estimation problem is actually a semi-infinite programming problem. Our recently developed dual parameterization method is applied for solving the problem. Computer numerical simulation results show that the semi-infinite programming approach outperforms the least squares approach.
URI: https://repository.cihe.edu.hk/jspui/handle/cihe/2307
DOI: https://doi.org/10.1016/j.csda.2015.01.020
CIHE Affiliated Publication: No
Appears in Collections:CIS Publication

SFX Query Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.