QuadratiK
1.2.0Collection of Methods Constructed using Kernel-Based Quadratic Distances
Overview
It includes test for multivariate normality, test for uniformity on the d-dimensional Sphere, non-parametric two- and k-sample tests, random generation of points from the Poisson kernel-based density and clustering algorithm for spherical data. For more information see Saraceno G., Markatou M., Mukhopadhyay R. and Golzy M. (2024) doi:10.48550/arXiv.2402.02290 Markatou, M. and Saraceno, G. (2024) doi:10.48550/arXiv.2407.16374, Ding, Y., Markatou, M. and Saraceno, G. (2023) doi:10.5705/ss.202022.0347, and Golzy, M. and Markatou, M. (2020) doi:10.1080/10618600.2020.1740713.
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Health
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-2512 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1811 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 43%
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Package metadata
- First published
- 2024-02-23
- Total releases
- 6 / 2 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 75 KB / 3 files
- Download size
- 486 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet