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

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.

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Year of publication:	2015
Authors:	Ling, Bingo Wing-Kuen ; Ho, Charlotte Yuk-Fan ; Siu, Wan-Chi ; Dai, Qingyun
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 88.2015, C, p. 111-118
Publisher:	Elsevier
Subject:	Best linear near unbiased estimations \| Nonlinear signal models \| Semi-infinite programming \| Dual parameterization

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

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