A didactically motivated PLS prediction algorithm

Modeling, Identification and Control

Volumn 22, Issue 3, 2001, Pages 131-139

  Ergon, R ^a   Esbensen, K H ^a  

^a UNIVERSITY OF SOUTH EASTERN NORWAY   (Norway)

Author keywords

Kalman filtering; Latent variables models; PLS prediction

Indexed keywords

ALGORITHMS; CALIBRATION; KALMAN FILTERING; LEAST SQUARES APPROXIMATIONS; MATRIX ALGEBRA; VECTORS;

PARTIAL LEAST SQUARES REGRESSION (PLSR) ALGORITHMS;

REGRESSION ANALYSIS;

EID: 0035505186     PISSN: 03327353     EISSN: None     Source Type: Journal    
DOI: 10.4173/mic.2001.3.1     Document Type: Article

References (15)

1. A. weighted view on the partial least squares algorithm
2. Dynamic system multivariate calibration by system identification methods
3. Static PLSR optimization based on Kalman filtering theory and noise covariance estimation
4. Principles of proper validation
5. On the structure of partial least squares regression
6. Extracting information from spectrophotometric curves