Keywords
Partial least squares regressionMathematicsMultivariate statisticsChemometricsCalibrationConjugate gradient methodAlgorithmMatrix (chemical analysis)Least-squares function approximationApplied mathematicsStatisticsComputer scienceChemistry
Affiliated Institutions
Related Publications
Regression methods for high dimensional multicollinear data
To compare their performance on high dimensional data, several regression methods are applied to data sets in which the number of exploratory variables greatly exceeds the sampl...
A Comparison of Least Squares and Latent Root Regression Estimators
Miilticollinesrity among the columns of regressor variables is known to cause severe distortion of the least squares estimates of the parameters in a multiple linear regression ...
Partial least squares regression and projection on latent structure regression (PLS Regression)
Abstract Partial least squares (PLS) regression ( a.k.a. projection on latent structures) is a recent technique that combines features from and generalizes principal component a...
Least Median of Squares Regression
Abstract Classical least squares regression consists of minimizing the sum of the squared residuals. Many authors have produced more robust versions of this estimator by replaci...
Maximum likelihood fitting using ordinary least squares algorithms
Abstract In this paper a general algorithm is provided for maximum likelihood fitting of deterministic models subject to Gaussianâdistributed residual variation (including any t...
Publication Info
- Year
- 1987
- Type
- article
- Volume
- 2
- Issue
- 1-3
- Pages
- 187-197
- Citations
- 348
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
348
OpenAlex
Cite This
Rolf Manne
(1987).
Analysis of two partial-least-squares algorithms for multivariate calibration.
Chemometrics and Intelligent Laboratory Systems
, 2
(1-3)
, 187-197.
https://doi.org/10.1016/0169-7439(87)80096-5
Identifiers
- DOI
- 10.1016/0169-7439(87)80096-5