Multivariate data modeling using modified kernel partial least squares
- 1 February 2015
- journal article
- Published by Elsevier BV in Chemical Engineering Research and Design
- Vol. 94, 466-474
- https://doi.org/10.1016/j.cherd.2014.09.004
Abstract
No abstract availableKeywords
Funding Information
- National Science Fund for Distinguished Youth Scholars of China (61025014)
- National Natural Science Foundation of China (61074072, 61374120)
This publication has 31 references indexed in Scilit:
- Exploring nonlinear relationships in chemical data using kernel-based methodsChemometrics and Intelligent Laboratory Systems, 2011
- The boosting: A new idea of building modelsChemometrics and Intelligent Laboratory Systems, 2010
- Partial least squares regression and projection on latent structure regression (PLS Regression)WIREs Computational Statistics, 2010
- Theory of net analyte signal vectors in inverse regressionJournal of Chemometrics, 2003
- Net analyte signal calculation for multivariate calibrationChemometrics and Intelligent Laboratory Systems, 2003
- Stochastic gradient boostingComputational Statistics & Data Analysis, 2002
- A comparison of orthogonal signal correction and net analyte preprocessing methods. Theoretical and experimental studyChemometrics and Intelligent Laboratory Systems, 2001
- Simultaneous spectrophotometric-multivariate calibration determination of several components of ophthalmic solutions: phenylephrine, chloramphenicol, antipyrine, methylparaben and thimerosalTalanta, 2000
- An Enhanced Algorithm for Linear Multivariate CalibrationAnalytical Chemistry, 1998
- Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance SpectraApplied Spectroscopy, 1989