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

• 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

• Approximation of Geodesic Distances for Geometric Data Analysis

Differential geometry and data analysis

• Differential Geometry and Statistics, M.K. Murray, J.W. Rice, Chapman and Hall/CRC,

• Ridges in image and data analysis, David Eberly, Springer, 1996,