### Introduction

### Theory, Examples & Exercises

en:monte_carlo_r

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(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/monte_carlo_r.1548504057.txt.gz · Last modified: 2019/01/26 20:00 by David Zelený