At LHC start-up, the luminosity was not sufficient for ordinary calibrations with collision muons, and so alternative methods were developed.
Given the observed between-city heterogeneity, the complex, time-varying nature of the exposures and the lack of information on individual characteristics, which would be included as confounders in health models, standard error correction methods such as ordinary regression calibration could still yield biased estimates [ 62, 63].
The purpose of the method was to minimize the sample dataset size to map soil depth to petrocalcic horizon based on ordinary cokriging, five calibration sample sizes (returned by Conditioned Latin hypercube –cLHS-), and apparent electrical conductivity (ECa) or elevation as variables of auxiliary information.
In the following, we introduce an experimental setting that allows for the comparison of the Zero-Training approach with the ordinary approach including calibration.
For the biofilms in the calibration set, ordinary glass microscope slides were used since each biofilm was ultimately transferred from the substrate before Raman analysis, much like a plaque scraping might be transferred.
To obtain individual calibration equations, ordinary-least-squares (OLS) linear regression models were used.
Instead, the data was used for the calibration of an ordinary differential equations (ODE) model implemented to simulate the nitrogen removal processes that took place in the SBR.
For parametric models, such as ordinary differential equation (ODE) models, calibration can be performed e.g. by maximum likelihood estimation (MLE).
However, the reference value is reliable because the ordinary spinner magnetometer is routinely cross-calibrated using several calibration specimens.
The binding energy of the C 1 s (284.6 eV) was used for the energy calibration, as estimated for an ordinary surface contamination of samples handled under ambient conditions.
