کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1247998 | 1495922 | 2013 | 15 صفحه PDF | دانلود رایگان |
The successive projections algorithm (SPA) is a variable-selection technique that has attracted increasing interest in the analytical-chemistry community in the past 10 years. The present review presents the basic features of SPA for Multiple Linear Regression (MLR) and Linear Discriminant Analysis (LDA) and reports some variants that have been proposed for sample selection, calibration transfer and Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) studies. We also discuss computational and pre-processing issues. By way of illustration we present two case studies involving near-infrared determination of protein in wheat and voltammetric classification of vegetable oils. The code employed in this article is freely available from us upon request.
► This is the first review of the Successive Projections Algorithm (SPA).
► We present the features of SPA for multivariate calibration and classification.
► We discuss SPA variants for calibration transfer and QSAR/QSPR studies.
► We analyze computational and pre-processing issues associated with SPA.
► We present case studies involving multivariate calibration and classification.
Journal: TrAC Trends in Analytical Chemistry - Volume 42, January 2013, Pages 84–98