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  2. Correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Correspondence_analysis

    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.

  3. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    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 .

  4. WordStat - Wikipedia

    en.wikipedia.org/wiki/WordStat

    Topic modeling to extract the main themes using NNMF and Factor Analysis. Correspondence analysis in order to identify words or concepts (or content categories) associated with any categorical meta-data associated with documents. Pre-and post-processing with R and python script; Analyze more than 70 languages including Chinese, Japanese, Korean ...

  5. Detrended correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Detrended_correspondence...

    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.

  6. Canonical correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Canonical_correspondence...

    In multivariate analysis, canonical correspondence analysis (CCA) is an ordination technique that determines axes from the response data as a unimodal combination of measured predictors. CCA is commonly used in ecology in order to extract gradients that drive the composition of ecological communities.

  7. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Canonical (or "constrained") correspondence analysis (CCA) for summarising the joint variation in two sets of variables (like redundancy analysis); combination of correspondence analysis and multivariate regression analysis. The underlying model assumes chi-squared dissimilarities among records (cases).

  8. Canonical correlation - Wikipedia

    en.wikipedia.org/wiki/Canonical_correlation

    In statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices.If we have two vectors X = (X 1, ..., X n) and Y = (Y 1, ..., Y m) of random variables, and there are correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y that have a maximum ...

  9. KH Coder - Wikipedia

    en.wikipedia.org/wiki/KH_Coder

    KH Coder is an open source software for computer assisted qualitative data analysis, particularly quantitative content analysis and text mining. It can be also used for computational linguistics. It supports processing and etymological information of text in several languages, such as Japanese, English, French, German, Italian, Portuguese and ...