Performances of several methods currently used for detection of discordant observations are reviewed in terms of a data set pertaining to absolute measurements of gravity acceleration, showing some peculiar features. Along with currently used methods a criterion based upon distribution of extremes is also relied upon to provide references; a modification of a simple, broadly used method is mentioned, improving performances while retaining inherent ease of use. Identification of distributions underlying experimental data may entail a substantial uncertainty component, particularly when sample size is small, and no mechanistic models are available. A pragmatic approach is described, providing to a first approximation estimation of overall uncertainty, inclusive of components pertaining to both estimation of parameters, and identification of distribution shape.
Approaches to handling discordant observations: an appraisal / Barbato, G; Genta, G; Germak, ALESSANDRO FRANCO LIDIA; Levi, R; Vicario, G.. - (2010). (Intervento presentato al convegno ENBIS-IMEKO TC 21 Workshop - Measurement Systems and Process Improvement (MSPI 2010) tenutosi a Teddington (UK) nel 19-20 aprile 2010).
Approaches to handling discordant observations: an appraisal
GERMAK, ALESSANDRO FRANCO LIDIA;
2010
Abstract
Performances of several methods currently used for detection of discordant observations are reviewed in terms of a data set pertaining to absolute measurements of gravity acceleration, showing some peculiar features. Along with currently used methods a criterion based upon distribution of extremes is also relied upon to provide references; a modification of a simple, broadly used method is mentioned, improving performances while retaining inherent ease of use. Identification of distributions underlying experimental data may entail a substantial uncertainty component, particularly when sample size is small, and no mechanistic models are available. A pragmatic approach is described, providing to a first approximation estimation of overall uncertainty, inclusive of components pertaining to both estimation of parameters, and identification of distribution shape.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.