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- Canonical_correspondence_analysis abstract "In applied statistics, canonical correspondence analysis (CCA) is a multivariate constrained ordination technique that extracts major gradients among combinations of explanatory variables in a dataset. The requirements of a CCA are that the samples are random and independent and that the independent variables are consistent within the sample site and error-free.".
- Canonical_correspondence_analysis wikiPageID "40892755".
- Canonical_correspondence_analysis wikiPageRevisionID "584168337".
- Canonical_correspondence_analysis subject Category:Statistical_methods.
- Canonical_correspondence_analysis comment "In applied statistics, canonical correspondence analysis (CCA) is a multivariate constrained ordination technique that extracts major gradients among combinations of explanatory variables in a dataset. The requirements of a CCA are that the samples are random and independent and that the independent variables are consistent within the sample site and error-free.".
- Canonical_correspondence_analysis label "Canonical correspondence analysis".
- Canonical_correspondence_analysis sameAs m.0ynyrv8.
- Canonical_correspondence_analysis sameAs Q16851643.
- Canonical_correspondence_analysis sameAs Q16851643.
- Canonical_correspondence_analysis wasDerivedFrom Canonical_correspondence_analysis?oldid=584168337.
- Canonical_correspondence_analysis isPrimaryTopicOf Canonical_correspondence_analysis.