COMPOUND-MODELLING OF METROLOGICAL DATA SERIES

In metrology the measurements on the same standard are usually repeated several times in each Laboratory. Repeating measurements is also the idea behind making inter-comparisons in different Laboratories of standards of a physical or chemical quantity. Often, whether these results can, or not, be considered as repeated measurements is not obvious, so that the statistical treatment of the data as they are repeated data can bring to misleading results. The paper reviews the use of two classes of methods keeping track of the fact that the data are collected in series: a) those considering a class of regression models able to accommodate both the commonality of all series and the specificity of each series; b) those using the mixture probability model for describing the pooled statistical distribution when the data series are provided in a form representing their statistical variability. Some problems related to the uncertainty estimate of the latter are also introduced.