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 Calibra...

When applying a statistical method in practice it often occurs that some observations deviate from the usual assumptions. However, many classical methods are sensitive to outliers. The goal of robust statistics is to develop methods that are robust against the possibility that one or several unannounced outliers may occur anywhere in the data. These methods then allow to detect outlying observa...

One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to ...

Digital Fourier filtering is used to produce a temperature-insensitive univariate calibration model for measuring lysozyme in aqueous solutions. Absorbance spectra over the 5000-4000 cm-1 spectral range are collected for lysozyme standards maintained at 14 degrees C. These spectra are used to compute the calibration model while a set of spectra collected at temperatures ranging from 4 to 24 deg...

The complexity of relationships between variables in a variety of rehabilitation settings can be appropriately addressed by the use of multivariate methods of statistical analysis. The purpose of this article is to describe (a) some basic concepts and principles of multivariate methods as well as (b) common misconceptions in the application of such methods. Specifically, the authors focus on th...