<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis, principal components analysis, principal components regression, N-way principal components analysis, partial least squares regression and self-organizing maps with respect to their possible application in intelligent analysis, classification, modelling and interpretation to environmental monitoring data. The target group of possible users is master program students (environmental chemistry, analytical chemistry, environmental modelling and risk assessment etc.).</p></abstract>

The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis, principal components analysis, principal components regression, N-way principal components analysis, partial least squares regression and self-organizing maps with respect to their possible application in intelligent analysis, classification, modelling and interpretation to environmental monitoring data. The target group of possible users is master program students (environmental chemistry, analytical chemistry, environmental modelling and risk assessment etc.).

Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students

University of Sofia “St. Kl. Okhridski”

Chemistry-Didactics-Ecology-Metrology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The present introductory course of lectures summarizes the principles and algorithms of several widely used multivariate statistical methods: cluster analysis,...

Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students

Publié en ligne: 29 janv. 2021

Pages: 35 - 56

DOI: https://doi.org/10.2478/cdem-2020-0002

Mots clés
chemometrics, environmetrics, exploratory data analysis (EDA), master students course

© 2020 Vasil Simeonov, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Basic Multivariate Statistical Methods for Environmental Monitoring Data Mining: Introductory Course for Master Students

Publié en ligne: 29 janv. 2021

Pages: 35 - 56

DOI: https://doi.org/10.2478/cdem-2020-0002

Mots cléschemometrics, environmetrics, exploratory data analysis (EDA), master students course

© 2020 Vasil Simeonov, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
chemometrics, environmetrics, exploratory data analysis (EDA), master students course