With a view to ensuring the validity of multivariate calibration models in the presence of temperature variations, a new methodology, individual contribution standardization (ICS), is proposed to correct for temperature-induced spectral variations. The methodology was applied to shortwave NIR spectral data sets recorded at different temperatures. The results showed that ICS can almost eliminate...

A new method for the elimination of uninformative variables in multivariate data sets is proposed. To achieve this, artificial (noise) variables are added and a closed form of the PLS or PCR model is obtained for the data set containing the experimental and the artificial variables. The experimental variables that do not have more importance than the artificial variables, as judged from a crite...

A new method for multivariate calibration [1 – 3] eliminates many of the problems associated with traditional methods, making the process easier and more transparent to the user. It uses physical methods to estimate the spectral signal and statistical methods to estimate noise. It is also less expensive to apply than partial least squares (PLS) or principal component regression (PCR) calibratio...

Introduction: ChemCam is an active remote sensing instrument suite being built for MSL [1,2]. It uses laser pulses to remove dust and to profile through weathering coatings of rocks up to 9 m away. Laser-induced breakdown spectroscopy (LIBS) obtains emission spectra of materials ablated from the samples in electronically excited states over an analysis spot < 1 mm in diameter at the focal point...

the potential of near infrared reflectance spectroscopy (nirs) as a fast method to predict the crude protein (cp) and moisture (m) content in fishmeal by scanning spectra between 1000 and 2500 nm using multivariate regression technique based on partial least squares (pls) was evaluated. the coefficient of determination in calibration (r2c) and standard error of calibration (sec) were 0.95 and 1...

Background: Two simple, precise and accurate multivariate calibration methods, partial least square (PLS) and principal component regression (PCR) have been applied for the simultaneous determination and dissolution profile evaluation of atorvastatin (ATV) and ezetimibe (EZT) in their binary mixtures and commercial tablets. Due to the closely overlapping spectral bands of the mentioned drugs, s...

This chapter is concered with how to calibrate a computer model to observational data when the model produces multivariate output and is temporally expensive to run. The significance of considering models with long run times is that they can only be run at a limited number of different inputs, ruling out a brute-force Monte Carlo approach. Consequently, all inference must be done with a limited...

Traditionally multivariate calibration models have been developed using regression based techniques including principal component regression and partial least squares and their non-linear counterparts. This paper proposes the application of Gaussian process regression as an alternative method for the development of a calibration model. By formulating the regression problem in a probabilistic fr...