Book Reviews: A User-Friendly Guide to Multivariate Calibration and Classification, An Academic Addition to the NIR Bookshelf

By Paul Geladi, T. Davies. 2002

1,315 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

focal point review (2012, neutral): “methods that have been thoroughly described in the literature.(27) Reducing”
Nondestructive estimation of Pinus taeda L. wood properties for samples from a wide range of sites in Georgia (2005, methodology): “2a) using the MSC math treatment and the standardized residual plot (Fig.”
Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials. (2014, methodology): “More detail on the principles of these methods can be found in Osborne et al. 20 and Næs et al. 24 During development of multivariate calibrations, a crucial aspect to consider is the correct selection of calibration and validation samples.”
Prediction of grain yield using reflectance spectra of canopy and leaves in maize plants grown under different water regimes (2012, background): “Partial least square regression (PLSR) decomposes the variability of the spectrum matrix into a small number of factors to describe the response variable (Naes et al., 2004) and may provide a more suitable alternative to stepwise regression for the identification of key wavelengths within the entire”
Non-destructive characterization and quality control of intact strawberries based on NIR spectral data (2012, methodology): “Discriminant models were constructed to classify strawberries by variety, using PLS discriminant analysis (PLS-DA) for supervised classification (Naes et al., 2002).”