Best linear near unbiased estimation for nonlinear signal models via semi-infinite programming approach

Author(s)
Author(s)
Ling, B. W.-K.
Ho, C. Y.-F.
Dai, Q.
Date Issued
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
DOI
SFU Affiliated Publication
No
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