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Publication Citation: On Non-Linear Estimation of a Measurand

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Author(s): Chih-Ming Wang; Hariharan K. Iyer;
Title: On Non-Linear Estimation of a Measurand
Published: November 07, 2011
Abstract: We consider an estimation problem described in the Guide to the Expression of Uncertainty in Measurement (GUM). The problem is concerned with estimating a measurand that is a non-linear function of input quantities. The GUM describes two methods for estimating the measurand -- method 1 is based on the same non-linear function of input-quantity estimates and method 2 is based on the mean of that function of individual measurements. We use several examples to compare the two methods based on their mean-squared errors and to demonstrate that a uniformly preferred method may not be available except for the simplest cases. We also consider an approach based on the Monte Carlo method in Supplement 1 of the GUM for the problem and compare it with the two methods.
Citation: Metrologia
Volume: 49
Pages: pp. 20 - 26
Keywords: GUM, mean-squared error, ratio estimation, simulation.
Research Areas: Statistics