Geometric data analysis
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Geometric data analysis comprises geometric aspects of image analysis, pattern analysis, and shape analysis, and the approach of multivariate statistics, which treat arbitrary data sets as clouds of points in a space that is n-dimensional. This includes topological data analysis, cluster analysis, inductive data analysis, correspondence analysis, multiple correspondence analysis, principal components analysis and iconography of correlations.
See also
[edit | edit source]- Algebraic statistics for algebraic-geometry in statistics
- Combinatorial data analysis
- Computational anatomy for the study of shapes and forms at the morphome scale
- Structured data analysis (statistics)
References
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- Approximation of Geodesic Distances for Geometric Data Analysis
Differential geometry and data analysis
[edit | edit source]- Differential Geometry and Statistics, M.K. Murray, J.W. Rice, Chapman and Hall/CRC, Lua error in Module:Citation/CS1/Configuration at line 2172: attempt to index field '?' (a nil value).
- Ridges in image and data analysis, David Eberly, Springer, 1996, Lua error in Module:Citation/CS1/Configuration at line 2172: attempt to index field '?' (a nil value).