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en:varpart_r [2019/04/06 18:01]
David Zelený [R functions]
en:varpart_r [2019/04/06 18:03]
David Zelený [R functions]
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 [[{|width: 7em; background-color:​ white; color: navy}varpart_exercise|Exercise {{::​lock-icon.png?​nolink|}}]] [[{|width: 7em; background-color:​ white; color: navy}varpart_exercise|Exercise {{::​lock-icon.png?​nolink|}}]]
 ==== R functions ==== ==== R functions ====
-  * **''​varpart''​** (library ''​vegan''​) - variation partitioning (using RDA, CCA or db-RDA) among up to four matrices of environmental variables. First argument (''​Y''​) is dependent variable, usually the matrix of species composition (the function calculates RDA, or, if ''​chisquare = TRUE'',​ CCA), but could be also only a single variable (in that case it calculates linear regression) or distance matrix (applying db-RDA using the function ''​capscale''​). Further arguments (up to four) are (groups of) explanatory variables. The function uses either formula interface (with ~, see [[en:​varpart_examples|examples]]) or matrices. The interpretation should be based on adjusted R<​sup>​2</​sup>,​ although raw R<​sup>​2</​sup>​ is also reported (for CCA, adjusted R2 is calculated by permutation method of Peres-Neto et al. 2006 and may slightly vary between re-analyses of the same data).+  * **''​varpart''​** (library ''​vegan''​) - variation partitioning (using RDA, CCA or db-RDA) among up to four matrices of environmental variables. First argument (''​Y''​) is dependent variable, usually the matrix of species composition (the function calculates RDA, or, if ''​chisquare = TRUE'',​ CCA), but could be also only a single variable (in that case it calculates linear regression) or distance matrix (applying db-RDA using the function ''​capscale''​). Further arguments (up to four) are (groups of) explanatory variables. The function uses either formula interface (with ~, see [[en:​varpart_examples|examples]]) or matrices. The interpretation should be based on adjusted R<​sup>​2</​sup>,​ although raw R<​sup>​2</​sup>​ is also reported (for CCA, adjusted R2 is calculated by permutation method of Peres-Neto et al. 2006 and may slightly vary between re-analyses of the same data; the argument ''​permutations''​ specifies the number of permutations used to calculate adjusted R<​sup>​2</​sup>​ in CCA).
   * **''​plot.varpart''​** (library ''​vegan''​) - draws Venn's diagram with fractions of explained variation. In default setting it doesn'​t show negative values of explained variation (argument ''​cutoff = 0''​). The function can use arguments of ''​showvarparts''​ below, e.g. to add the labels for individual (groups of) variables (''​Xnames''​),​ or colors of the fractions (''​bg''​). Consult ''?​plot.varpart''​ for more details.   * **''​plot.varpart''​** (library ''​vegan''​) - draws Venn's diagram with fractions of explained variation. In default setting it doesn'​t show negative values of explained variation (argument ''​cutoff = 0''​). The function can use arguments of ''​showvarparts''​ below, e.g. to add the labels for individual (groups of) variables (''​Xnames''​),​ or colors of the fractions (''​bg''​). Consult ''?​plot.varpart''​ for more details.
   * **''​showvarparts''​** ​ (library ''​vegan''​) - draws schema of Venn's diagram with codes of individual fractions.   * **''​showvarparts''​** ​ (library ''​vegan''​) - draws schema of Venn's diagram with codes of individual fractions.
    
en/varpart_r.txt · Last modified: 2019/04/06 18:03 by David Zelený