2016/10/31 by Luca Lista
Agricultural and Biological Sciences · Decision Sciences · Mathematics · Physics and Astronomy · #Best linear unbiased prediction #Bias of an estimator #Estimator #Function (biology) #Iterative method #Measurement uncertainty #Pesticide Residue Analysis and Safety #Scientific Measurement and Uncertainty Evaluation #Statistical and numerical algorithms #Unbiased Estimation #physics.data-an
paper · pdf · doi:10.1051/epjconf/201713711006
published as EPJ Web of Conferences 137, 11006 (2017) · 10 pages, 4 figures, proceedings of the XIIth Quark Confinement and Hadron Spectrum conference, 28/8-2/9 2016, Tessaloniki, Greece
openalex created_date 2016/10/14 · arxiv created 2016/12/05 · openalex publication_date 2017/01/01 · arxiv updated 2017/03/28 · openalex updated_date 2026/08/05
The most accurate method to combine measurements from different experiments is to build a combined likelihood function and use it to perform the desired inference. This is not always possible for various reasons, hence approximate methods are often convenient. Among those, the best linear unbiased estimator (BLUE) is the most popular, allowing to take into account individual uncertainties and their correlations. The method is unbiased by construction if the true uncertainties and their correlations are known, but it may exhibit a bias if uncertainty estimates are used in place of the true ones, in particular if those estimated uncertainties depend on measured values. In those cases, an iterative application of the BLUE method may reduce the bias of the combined measurement.