Random-effects ordination: describing and predicting multivariate correlations and co-occurrences
Abstract
Ecology is inherently multivariate, but high-dimensional data are difficult to understand. Dimension reduction with ordination analysis helps with both data exploration and clarification of the meaning of inferences (e.g., randomization tests, variation partitioning) about a statistical population. Most such inferences are asymmetric, in that variables are classified as either response or explanatory (e.g., factors, predictors). But this...
Paper Details
Title
Random-effects ordination: describing and predicting multivariate correlations and co-occurrences
Published Date
Nov 1, 2011
Journal
Volume
81
Issue
4
Pages
635 - 663
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