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Multivariate Description. What Technique? Response variable(s)... Predictors(s) No Predictors(s) Yes... is one distribution summary regression models...

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Presentation on theme: "Multivariate Description. What Technique? Response variable(s)... Predictors(s) No Predictors(s) Yes... is one distribution summary regression models..."— Presentation transcript:

1 Multivariate Description

2 What Technique? Response variable(s)... Predictors(s) No Predictors(s) Yes... is one distribution summary regression models... are many indirect gradient analysis (PCA, CA, DCA, MDS) cluster analysis direct gradient analysis constrained cluster analysis discriminant analysis (CVA)

3 Raw Data

4 Linear Regression

5 Two Regressions

6 Principal Components

7 Gulls Variables

8 Scree Plot

9 Output > gulls.pca2$loadings Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Weight Wing Bill H.and.B > summary(gulls.pca2) Importance of components: Comp.1 Comp.2 Comp.3 Standard deviation Proportion of Variance Cumulative Proportion

10 Bi-Plot

11 Male or Female?

12 Linear Discriminant > gulls.lda <- lda(Sex ~ Wing + Weight + H.and.B + Bill, gulls) lda(Sex ~ Wing + Weight + H.and.B + Bill, data = gulls) Prior probabilities of groups: Group means: Wing Weight H.and.B Bill Coefficients of linear discriminants: LD1 Wing Weight H.and.B Bill

13 Discriminating

14 Relationship between PCA and LDA

15 CVA

16


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