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...

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...

In order to transfer a calibration model, techniques such as piecewise direct standardization (PDS) or direct standardization (DS) are used. This implies that the same subset of samples must be measured in both situations. However, when a model is transferred from an off-line application to an on-line application, it is not possible to remeasure the same subset of samples. In this paper, howeve...

PURPOSE Analysis of drugs in multicomponent system officially is carried out using chromatographic technique, however, this technique is too laborious and involving sophisticated instrument. Therefore, UV-VIS spectrophotometry coupled with multivariate calibration of partial least square (PLS) for quantitative analysis of metamizole, thiamin and pyridoxin is developed in the presence of cyanoco...

This paper investigates the use of genetic algorithm to optimize poses selection to improve kinematic calibration for manipulator. Genetic algorithm is used to determine the optimal poses while iterative least square algorithm is used to calibrate the kinematics model of the manipulator. Observability index are used to evaluate the optimality of the set of poses. The fitness function of genetic...

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...

• y(u) aims at reproducing some real phenomenon which we denote by y 1.2 Validation of computer models •Question of interest: Does the computer model adequately represent reality? •Obtain field data yi that results from observing reality in a physical experiment yFi = y +εi , εi ∼ Np(0,Σ F ), ,Σ = Λ R Λ, Λ = diag(σ i ) •Combine model and field data with a statistical model y = y(u) + b (Kennedy...