Project Status: Active – The project has reached a stable, usable state and is being actively developed.

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Collection of Methods Constructed using the Kernel-Based Quadratic Distances

provides the first implementation, in R and Python, of a comprehensive set of goodness-of-fit tests and a clustering technique for spherical data using kernel-based quadratic distances. This framework aims to bridge the gap between the statistical and machine learning literature. It includes:

Details

The work has been supported by Kaleida Health Foundation, National Science Foundation and Department of Biostatistics, University at Buffalo.

Authors

Giovanni Saraceno, Marianthi Markatou, Raktim Mukhopadhyay, Mojgan Golzy
Email: gsaracen@buffalo.edu

References