Geometric data analysis

Geometric data analysis comprises geometric aspects of image analysis, pattern analysis and shape analysis and the approach of multivariate statistics that treats arbitrary data sets as clouds of points in n-dimensional space. This includes topological data analysis, cluster analysis, inductive data analysis, correspondence analysis, multiple correspondence analysis, principal components analysis and fr:Iconographie des corrélations.^[clarify]

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[]

• Brigitte Le Roux, Henry Rouanet (2004). Geometric Data Analysis: from Correspondence Analysis to Structured Data Analysis. Springer. ISBN 978-1-4020-2235-7.
• Michael J. Greenacre, Jörg Blasius (2006). Multiple Correspondence Analysis and Related Methods. CRC press. ISBN 978-1-58488-628-0.
• 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, ISBN 978-0-412-39860-5
• Ridges in image and data analysis, David Eberly, Springer, 1996, ISBN 978-0-7923-4268-7