Principal Components
Demonstration Copy Vhs NTSC Video
1994
Elsevier Science Ltd (Hersteller)
978-0-444-81979-6 (ISBN)
Elsevier Science Ltd (Hersteller)
978-0-444-81979-6 (ISBN)
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A 25 minute demonstration video, containing a representative selection from the four videos comprising the complete set. These provide an introduction to the use of principal components analysis (PCA) and related methods in chemometrics.
This set, comprising 4 videos, a manual and a software package, is an introduction to the use of principal components analysis (PCA) and related methods in chemometrics. Emphasis has been placed on the use of PCA to display graphically the structure of data sets or to extract graphically information from such a set (display methods). However, links are provided to several other important methods, such as evolving factor analysis, principal component regression and partial least squares. In order to induce students to learn PCA, and convince them of the usefulness of the methods, several real-life examples have been included. These examples have been chosen to illustrate the generality of the data analysis approach. The data pertain to food, industrial and environmental analysis, animal experimentation, medicinal chemistry, virology and epidemiology. In the software section an additional example concerned with food analysis has been added. Section 3 of the manual contains a complete list of figures. This allows the user to look at some of the figures in a more leisurely fashion or to re-read text which has been heard when viewing the videos.
Some of the visuals and some of the texts (occasionally shortened) have been included in this section. Two types of software augment this series. The first is a tutorial version of a commercial software package called SPECTRAMAP, which has been modified for didactical use. SPECTRAMAP is a performant software for methods derived from PCA that gives excellent display quality. The other type of software is a listing of a MATLAB program. In order to understand completely a mathematical algorithm or method, the authors recommend the user to program it himself, using MATLAB. In this way the user can also obtain all the intermediate results, thereby understanding what happens with a data set when analyzed by PCA. This section also contains an additional data set with which the user can experiment with the software. Some hints are given in to teachers and self-learners on how to use the material to optimize results.
This set, comprising 4 videos, a manual and a software package, is an introduction to the use of principal components analysis (PCA) and related methods in chemometrics. Emphasis has been placed on the use of PCA to display graphically the structure of data sets or to extract graphically information from such a set (display methods). However, links are provided to several other important methods, such as evolving factor analysis, principal component regression and partial least squares. In order to induce students to learn PCA, and convince them of the usefulness of the methods, several real-life examples have been included. These examples have been chosen to illustrate the generality of the data analysis approach. The data pertain to food, industrial and environmental analysis, animal experimentation, medicinal chemistry, virology and epidemiology. In the software section an additional example concerned with food analysis has been added. Section 3 of the manual contains a complete list of figures. This allows the user to look at some of the figures in a more leisurely fashion or to re-read text which has been heard when viewing the videos.
Some of the visuals and some of the texts (occasionally shortened) have been included in this section. Two types of software augment this series. The first is a tutorial version of a commercial software package called SPECTRAMAP, which has been modified for didactical use. SPECTRAMAP is a performant software for methods derived from PCA that gives excellent display quality. The other type of software is a listing of a MATLAB program. In order to understand completely a mathematical algorithm or method, the authors recommend the user to program it himself, using MATLAB. In this way the user can also obtain all the intermediate results, thereby understanding what happens with a data set when analyzed by PCA. This section also contains an additional data set with which the user can experiment with the software. Some hints are given in to teachers and self-learners on how to use the material to optimize results.
Part 1 Videos: principal components as display method; display variables and relationships between variables and objects; singular value decomposition; eigen values; evolving factor analysis; software and exercises; the display of latent variables in tabulated data. Part 2 Manual: proposed didactical concepts; list of visuals; software section; 4A - SPECTRAMAP, P.J. Lewi et al; 4B - A MATLAB program for principal components analysis, M. Massart.
| Erscheint lt. Verlag | 31.7.1994 |
|---|---|
| Verlagsort | Oxford |
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Naturwissenschaften ► Chemie | |
| ISBN-10 | 0-444-81979-7 / 0444819797 |
| ISBN-13 | 978-0-444-81979-6 / 9780444819796 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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