### Introduction

### Theory, Examples & Exercises

en:expl_var_r

Section: Ordination analysis

(library`RsquareAdj`

`vegan`

) - extracts the value of R^{2}and adjusted R^{2}from results of ordination (and also regression). For linear constrained ordinations (RDA, tb-RDA), the adjusted R2 is calculated using Ezekiel's formula, while for unimodal constrained ordinations (CCA) the calculation is based on permutation model introduced by Peres-Neto et al. (2006).(library`anova.cca`

`vegan`

) - tests the significance of the variation in species composition explained by explanatory variables in constrained ordination (RDA, CCA), using Monte Carlo permutation test. It can test the significance of- the global model (default setting), i.e. all variables included in the analysis;
- only the first constrained axis (adding argument
`first = TRUE`

); - individual axes (
`by = “axis”`

), sequentially from the first to the last (this is done by using samples scores on the*n*-th axis as explanatory variables, while using scores of the axis 1, 2, ...*n*as covariables); - individual terms (explanatory variables) added sequentially in the order in which they appear in the formula or data frame (
`by = “terms”`

; note that this variation depends on the order of variables in which they enter the model); - variation explained by individual explanatory variables after removing variation of all other variables in the model (
`by = “margin”`

; here the variation does not depend on the order of variables in the model).

en/expl_var_r.txt · Last modified: 2019/02/26 23:35 by David Zelený