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Applied factor analysis in the natural sciences /
Applied factor analysis in the natural sciences

Author: Richard A. Reyment, K.H. J�oreskog ; appendix by Leslie F. Marcus. J�oreskog, K. G. ; R A Reyment; K G Jöreskog
Publisher: Cambridge [England] ; New York, NY, USA : Cambridge University Press, 1993.
Edition/Format:   Print book : English : 2nd edView all editions and formats
Summary:

Explores the application of eigenanalysis to statistical data from the natural sciences to achieve statistical reduction and to construct scientific models.

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Richard A. Reyment, K.H. J�oreskog ; appendix by Leslie F. Marcus. J�oreskog, K. G. ; R A Reyment; K G Jöreskog
ISBN: 0521412420 9780521412421 9780511524882 0511524889
OCLC Number: 26635568
Description: xii, 371 pages : illustrations ; 24 cm
Contents: 1. Introduction --
1.1. Structure in multivariate data --
1.2. An example of principal component factor analysis --
1.3. Overview of problems amenable to treatment by factor-analytical techniques --
2. Basic Mathematical and Statistical Concepts --
2.2. Geometrical interpretation of data matrices --
2.3. Elementary vector operations --
2.4. The geometry of vectors --
2.5. Types of matrices --
2.6. Elementary matrix arithmetic --
2.7. Normal and orthonormal vectors and matrices --
2.8. Descriptive statistics in matrix notation --
2.9. Rotation of coordinate systems --
2.10. The structure of a matrix --
2.11. Eigenvalues and eigenvectors --
2.12. Basic structure of a matrix and the Eckart-Young theorem --
2.13. Least-squares properties of eigenvalues and eigenvectors --
2.14. Canonical analysis of asymmetry --
3. Aims, Ideas, and Models of Factor Analysis --
3.2. Fixed and random cases --
3.3. Discussion of models --
3.4. Model of the variances and covariances --
3.5. Principal component versus true factor analysis --
3.6. Transformational indeterminacy of factors --
3.7. Factor pattern and factor structure --
3.8. Example of true factor analysis --
3.9. Representation of results --
3.10. True factor analysis summarized --
4. R-Mode Methods --
4.2. Principal component analysis --
4.3. True factor analysis --
4.4. Robust principal component analysis --
4.5. Principal component analysis and cross-validation --
4.6. Principal component analysis of compositional data --
4.7. Path analysis and Wrightian factor analysis --
5. Q-Mode Methods --
5.2. Principal coordinates --
5.3. Logcontrast principal coordinate analysis --
5.4. Q-mode factor analysis --
5.5. The analysis of asymmetry --
6. Q-R-Mode methods --
6.1. Correspondence analysis --
6.2. Comparison of Q-modes methods and correspondence analysis --
6.3. The Gabriel biplot method --
6.4. Canonical correlation analysis --
7. Steps in the Analysis --
7.2. Objectives --
7.3. Categories of data --
7.4. The data matrix --
7.5. Selection of the measure of association --
7.6. Choice of the factor method --
7.7. Selection of the number of factors --
7.8. Rotation of factor axes --
7.9. Factor scores --
8. Examples and Case Histories --
8.2. R-mode principal components in mineral chemistry --
8.3. R-mode factor analysis in paleoecology --
8.4. R-mode factor analysis in sedimentology --
8.5. R- and Q-mode analyses in subsurface brine geochemistry --
8.6. Imbrie Q-mode factor analysis in sedimentology --
8.7. Imbrie Q-mode factor analysis in foraminiferal ecology --
8.8. Principal coordinate analysis of soils --
8.9. Q-R-mode analysis of maturation of crude oils --
8.10. Correspondence analysis of metamorphic rocks --
8.11. True factor analysis in marine ecology --
8.12. A problem in soil science --
8.13. The method of principal warps --
8.14. Two simple case histories --
Appendix: Computer programs / Leslie F. Marcus.
Responsibility: Richard A. Reyment, K.G. Jöreskog ; appendix by Leslie F. Marcus.
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'Overall I found this to be an excellent volume and would certainly recommend it to anyone who wishes to understand factor analysis in the wide sense, whatever their background discipline.' David J. Read more...

 
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