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Applying topological data analysis ball mapper in Stata

Author

Listed:
  • Simon Rudkin

    (University of Manchester)

  • Wanling Rudkin

    (University of Exeter)

Abstract

Multivariate datasets are mappable to a multidimensional space in which the coordinate of a data point in each dimension corresponds to the value of a given variable observed for that data point. In two dimensions, with two variables, the result is a scatterplot. Extending the number of variables creates a visualization challenge. This presentation introduces the ballmapper package for implementing topological data analysis ball mapper (TDABM) in Stata. TDABM creates an abstract, topologically faithful, two-dimensional visualization of a dataset without requiring dimensionality reduction or information loss. The value of TDABM is being realized by a growing corpus of applications papers in the humanities and natural sciences. First, the need for TDABM is introduced. Second, the TDABM algorithm is briefly explained through illustrations from the Stata package. Finally, an example implementation is shown such that users can understand how to visualize their own data in Stata.

Suggested Citation

  • Simon Rudkin & Wanling Rudkin, 2026. "Applying topological data analysis ball mapper in Stata," UK Stata Conference 2026 09, Stata Users Group.
    • Handle: RePEc:boc:lsug26:09
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