For Correspondence Analysis we have a term and definition in Ordination.

Correspondence Analysis (Ordination)

An eigenanalysis-based ordination method, also known as reciprocal averaging. See Correspondence Analysis.
* Correspondence Analysis has been discovered independently by different scientists.
* Reciprocal Averaging means that sample scores are calculated as a weighted average (or centroid) of species scores, and species scores are calculated as a weighted average (or centroid) of sample scores, and iterations continue until there is no change. However, other algorithms are possible.
* Correspondence Analysis simultaneously ordinates species and samples. There are as many axes as there are species or samples, whichever is less.
* The number of axes worth interpreting is a matter of taste, but the size of eigenvalues can be a guide.
* Correspondence Analysis maximizes the correlation between species scores and sample scores. The eigenvalue is equal to the correlation coefficient. The eigenvectors are either species scores or sample scores.
* An eigenvalue of 1.0 implies that one sample (or group of samples) shares no species with all other samples.
* One can put new points in a Correspondence Analysis without affecting the ordination.
* As with all the other eigenanalysis techniques, it is possible to define "passive samples" or "passive species".
* Correspondence Analysis has a problem called the arch effect. This effect is caused by nonlinearity of species response curves.
* The arch is not as serious as the horseshoe effect of PCA, because the ends of the gradient are not convoluted.
* Another related problem of Correspondence Analysis is that the ends of the gradient are compressed.
* Detrended Correspondence Analysis was designed to correct for the arch effect and gradient compression, as described above.

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