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Correspondence analysis (CA) is a multivariate statistical technique proposed [1] by Herman Otto Hartley (Hirschfeld) [2] and later developed by Jean-Paul Benzécri. [3] It is conceptually similar to principal component analysis, but applies to categorical rather than continuous data.
Ordination methods can broadly be categorized in eigenvector-, algorithm-, or model-based methods. Many classical ordination techniques, including principal components analysis, correspondence analysis (CA) and its derivatives (detrended correspondence analysis, canonical correspondence analysis, and redundancy analysis, belong to the first group).
Note the asymmetry in this latter definition; which talks about a correspondence from X to Y rather than a correspondence between X and Y. The typical example of the latter kind of correspondence is the graph of a function f:X→Y. Correspondences also play an important role in the construction of motives (cf. presheaf with transfers). [2]
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space .
Time series: random data plus trend, with best-fit line and different applied filters. In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time.
Detrended correspondence analysis (DCA) is a multivariate statistical technique widely used by ecologists to find the main factors or gradients in large, species-rich but usually sparse data matrices that typify ecological community data.
Correspondence (algebraic geometry), between two algebraic varieties; Corresponding sides and corresponding angles, between two polygons; Correspondence (category theory), the opposite of a profunctor; Correspondence (von Neumann algebra) or bimodule, a type of Hilbert space; Correspondence analysis, a multivariate statistical technique
A bijection, bijective function, or one-to-one correspondence between two mathematical sets is a function such that each element of the second set (the codomain) is the image of exactly one element of the first set (the domain).