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Acknowledgements
Introduction
1. Installing and Running Software
2. Reproducible Research
3. Loading Data
4. R Basics
5. Data Adjustments
6. Transformations
7. Relativizations
8. Matrix Algebra Basics
9. Matrix Algebra to Solve a Linear Regression
10. Eigenanalysis
11. Properties of Distance Measures
12. Common Distance Measures
13. Multivariate Outlier Analysis
14. ANOVA / MANOVA
15. Sample Datasets
16. Permutation Tests
17. ANOSIM
18. Mantel Test
19. MRPP
20. PERMANOVA
21. PERMDISP
22. RRPP
23. GDM
24. Complex Models
25. Controlling Permutations
26. Restricting Permutations
27. Comparison of Techniques
28. Types of Cluster Analyses
29. Hierarchical Cluster Analysis
30. k-Means Cluster Analysis
31. Using Groups
32. Discriminant Analysis
33. Overview of Classification and Regression Trees
34. Univariate Regression Trees
35. Multivariate Regression Trees
36. Types of Ordination Methods
37. PCA
38. NMDS
39. PCoA
40. RDA and dbRDA
41. CA, DCA, and CCA
42. Comparison of Ordination Techniques
43. General Graphing Principles
44. Visualizing and Interpreting Ordinations
45. SIMPER
46. ISA
47. TITAN
Appendix 1: Order of Data Adjustments
Appendix 2: Structure of Complex Experimental Designs
Appendix 4: Contrasts
Group Comparisons
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Applied Multivariate Statistics in R Copyright © 2024 by Jonathan D. Bakker is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.