### Introduction

### Theory, Examples & Exercises

en:rda_cca_r

**This is an old revision of the document!**

- this function calculates RDA if matrix of environmental variables is supplied (if not, it calculates PCA). Two types of syntax are available:`rda`

- matrix syntax -
`RDA = rda (Y, X, W)`

, where`Y`

is the response matrix (species composition),`X`

is the explanatory matrix (environmental factors) and`W`

is the matrix of covariables - formula syntax -
`RDA = rda (Y ~ var1 + factorA + var2*var3 + Condition (var4), data = XW)`

- as explanatory are used: quantitative variable`var1`

, categorical variable`factorA`

, interaction term between`var2`

and`var3`

, whereas`var4`

is used as covariable and hence partialled out.

- this function calculates CCA if matrix of environmental variables is supplied (if not, it calculates CA).`cca`

- in case of CCA, it extracts only the value of R`RsquareAdj`

^{2}, while values of adjusted R^{2}are not available (these need to be calculated by permutations and it is not available in R yet).- tests the significance of the variation in species composition explained by explanatory variables, using Monte Carlo permutation test.`anova.cca`

en/rda_cca_r.1548499018.txt.gz · Last modified: 2019/01/26 18:36 by David Zelený