In the multivariate calibration framework we revisit and investigate the prediction performance of three high-dimensional modeling strategies: partial least squares, principal component regression and P-spline signal regression. Specifically we are interested in comparing the stability and robustness of prediction under differing conditions, e.g. training the model under one temperature and usi...

In multivariate calibrations usually a minimal residual error in the model’s predictions is aimed at, while generally less attention is paid to the robustness of the model with respect to changes in instrumentation, laboratory conditions, or sample composition. In this paper, we propose a strategy for selecting a multivariate calibration model which possesses a small prediction error and, simul...

Article history: In general, linearity is assum Received 16 November 2008 Received in revised form 20 January 2009 Accepted 3 February 2009 Available online 12 February 2009

The recent improvements of Graphics Processing Units (GPU) have provided to the bio-inspired algorithms a powerful processing platform. Indeed, a lot of highly parallelizable problems can be significantly accelerated using GPU architecture. Among these algorithms, the Firefly Algorithm (FA) is a newly proposed method with potential application in several real world problems such as variable sel...