Fast regression methods in a Lanczos (or PLS-1) basis. Theory and applications
- 24 July 2000
- journal article
- Published by Elsevier in Chemometrics and Intelligent Laboratory Systems
- Vol. 51 (2) , 145-161
- https://doi.org/10.1016/s0169-7439(00)00063-0
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- Cyclic subspace regression with analysis of the hat matrixChemometrics and Intelligent Laboratory Systems, 1999
- Comparison of Prediction- and Correlation-Based Methods to Select the Best Subset of Principal Components for Principal Component Regression and Detect Outlying ObjectsApplied Spectroscopy, 1998
- Cyclic Subspace RegressionJournal of Multivariate Analysis, 1998
- Two data sets of near infrared spectraPublished by Elsevier ,1998
- Kernel-PCA algorithms for wide data Part II: Fast cross-validation and application in classification of NIR dataChemometrics and Intelligent Laboratory Systems, 1997
- The kernel PCA algorithms for wide data. Part I: Theory and algorithmsChemometrics and Intelligent Laboratory Systems, 1997
- A correlation principal component regression analysis of NIR dataJournal of Chemometrics, 1995
- Which principal components to utilize for principal component regressionJournal of Chemometrics, 1992
- Analysis of two partial-least-squares algorithms for multivariate calibrationChemometrics and Intelligent Laboratory Systems, 1987
- An iteration method for the solution of the eigenvalue problem of linear differential and integral operatorsJournal of Research of the National Bureau of Standards, 1950