Abstract
The present work describes a MATLAB graphical user interface for the Successive Projections Algorithm (SPA), which is a variable selection technique aimed at reducing collinearity problems in Multiple Linear Regression (MLR) modelling. The interface also offers the possibility of pre-processing the data using Savitzky–Golay smoothing/differentiation and/or wavelet denoising. Sample selection routines for dividing the samples into calibration and validation sets are also implemented. At the end, prediction statistics (PRESS, RMSEP, SDV, BIAS and correlation coefficient) are calculated to evaluate the performance of the resulting MLR model. All these operations can be carried out by the user without the need for MATLAB programming skills. For illustration, an example involving near-infrared spectrometric determination of moisture in corn samples is presented. The software is freely available at www.ele.ita.br/~kawakami/spa
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