Sentence examples for multivariate calibration models from inspiring English sources

The development of reliable multivariate calibration models is generally time-consuming and costly.

Multivariate calibration models were carried out including partial least squares regression (PLS) and interval partial least-squares (iPLS).

Quantification of the enzymatically released monosaccharides by HPLC was used to design multivariate calibration models (biPLS) on the NIR spectra.

First-order multivariate calibration models were built using net analyte pre-processing followed by classical least-squared regression (NAP/CLS) method.

An improved genetic algorithms (GAs) is used to implement an automated wavelength selection procedure for use in building multivariate calibration models based on partial least squares regression.

Wavelet analysis is developed as a preprocessing tool for use in removing background information from near-infrared (near-IR) single-beam spectra before the construction of multivariate calibration models.

However, any change in the instrumental response or variations in the measurement conditions can render a multivariate calibration model invalid.

Therefore, once a reliable multivariate calibration model is established, it is expected to be used for an extended period.

The evaluation of a candidate sensor array is based on its multivariate calibration model, which is efficiently estimated from well-designed simulation experiments.

The specific application in this case was to determine the root cause for a bias found during the development of a multivariate calibration model for a Near Infrared (NIR) instrument.

Therefore, the objective of this study was to develop and validate a multivariate calibration model in association with the near infrared spectroscopy technique (NIR) for the simultaneous determination of rifampicin, isoniazid, pyrazinamide and ethambutol.