David Zelený

en:expl_var_r

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 en:expl_var_r [2019/02/10 16:07]David Zelený en:expl_var_r [2019/02/10 16:19]David Zelený [Explained variation and Monte Carlo permutation test (constrained ordination)] Both sides previous revision Previous revision 2019/02/26 23:35 David Zelený 2019/02/10 16:19 David Zelený [Explained variation and Monte Carlo permutation test (constrained ordination)] 2019/02/10 16:07 David Zelený 2019/02/10 16:04 David Zelený 2019/01/26 20:04 David Zelený [Explained variance (constrained ordination)] 2019/01/26 19:50 David Zelený 2017/10/11 20:36 external edit2017/05/02 00:43 David Zelený created 2019/02/26 23:35 David Zelený 2019/02/10 16:19 David Zelený [Explained variation and Monte Carlo permutation test (constrained ordination)] 2019/02/10 16:07 David Zelený 2019/02/10 16:04 David Zelený 2019/01/26 20:04 David Zelený [Explained variance (constrained ordination)] 2019/01/26 19:50 David Zelený 2017/10/11 20:36 external edit2017/05/02 00:43 David Zelený created Last revision Both sides next revision Line 7: Line 7: [[{|width: 7em; background-color:​ white; color: navy}expl_var_exercise|Exercise {{::​lock-icon.png?​nolink|}}]] [[{|width: 7em; background-color:​ white; color: navy}expl_var_exercise|Exercise {{::​lock-icon.png?​nolink|}}]] + ==== R functions ==== + + * **''​RsquareAdj''​** (library ''​vegan''​) - extracts the value of R<​sup>​2​ and adjusted R<​sup>​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 [[en:​references|Peres-Neto et al. (2006)]]. * **''​anova.cca''​** (library ''​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 * **''​anova.cca''​** (library ''​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; * the global model (default setting), i.e. all variables included in the analysis;