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en:varpart [2017/10/11 20:36] 127.0.0.1 external edit |
en:varpart [2019/02/25 20:57] (current) David Zelený |
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| - | ====== Constrained ordination ====== | + | Section: [[en:ordination]] |
| - | ===== Variation partitioning ===== | + | ===== Variation partitioning (constrained ordination) ===== |
| [[{|width: 7em; background-color: light; color: firebrick}varpart|**Theory**]] | [[{|width: 7em; background-color: light; color: firebrick}varpart|**Theory**]] | ||
| [[{|width: 7em; background-color: white; color: navy}varpart_R|R functions]] | [[{|width: 7em; background-color: white; color: navy}varpart_R|R functions]] | ||
| [[{|width: 7em; background-color: white; color: navy}varpart_examples|Examples]] | [[{|width: 7em; background-color: white; color: navy}varpart_examples|Examples]] | ||
| [[{|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|}}]] | ||
| - | ==== Theory ==== | + | |
| <wrap lo>Note: variation partitioning is sometimes also called **//commonality analysis//** in reference to the //common// (shared) fraction of variation (Kerlinger & Pedhazur 1973). It is also a synonym to **//variance partitioning//**((As to the distinction between //variance// and //variation//, Legendre & Legendre (2012) note: | <wrap lo>Note: variation partitioning is sometimes also called **//commonality analysis//** in reference to the //common// (shared) fraction of variation (Kerlinger & Pedhazur 1973). It is also a synonym to **//variance partitioning//**((As to the distinction between //variance// and //variation//, Legendre & Legendre (2012) note: | ||
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| *[d] - unexplained variation. | *[d] - unexplained variation. | ||
| - | If the variation is partitioned among groups with the same number of variables (e.g. two soil and two climatic variables), then variation explained by each group is comparable without adjustment. However, if groups contain different numbers of variables, variation explained by not adjusted R<sup>2</sup> is not comparable since R2 tends to increase with the number of explanatory variables. Here, use of adjusted R2 is recommended. | + | If the variation is partitioned among groups with the same number of variables (e.g. two soil and two climatic variables), then the variation explained by each group is comparable without adjustment. However, if groups contain different numbers of variables, variation explained by not adjusted R<sup>2</sup> is not comparable since R<sup>2</sup> tends to increase with the number of explanatory variables. Here, the use of adjusted R<sup>2</sup> is recommended. |
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| - | The library ''vegan'' offers function ''varpart'', which can partition variation among up to four variables (or groups of variables). Note that ''varpart'' is based on redundancy analysis (''rda'') and uses adjusted R<sup>2</sup> to express explained variation. The reason for using only ''rda'' is that in R, there is still no function available to calculate adjusted R<sup>2</sup> for unimodal ordination methods (like ''cca''). | + | |
en/varpart.1507725374.txt.gz · Last modified: 2017/10/11 20:36 by 127.0.0.1
