README.md

| Usage | Release | Development | |------------------|------------------------|------------------------------| | CRAN_Downloads_Badge License: GPL v3|arXiv CRAN version GitHub version | Project Status: Active – The project has reached a stable, usable state and is being actively developed. Status at rOpenSci Software Peer Review codecov R-CMD-check Lifecycle | |

Collection of Methods Constructed using the Kernel-Based Quadratic Distances

QuadratiK provides the first implementation, in R and Python, of a comprehensive set of goodness-of-fit tests and a clustering technique for $d$-dimensional spherical data $d \ge 2$ using kernel-based quadratic distances. It includes:

For an introduction to the usage of QuadratiK see the vignette Introduction to the QuadratiK Package.

Installation

You can install the version published on CRAN of QuadratiK

install.packages("QuadratiK")

or the development version on GitHub

library(devtools)
install_github('giovsaraceno/QuadratiK-package')

The QuadratiK package is also available in Python on PyPI https://pypi.org/project/QuadratiK/ and also as a Dashboard application. Usage instruction for the Dashboard can be found at https://quadratik.readthedocs.io/en/latest/user_guide/dashboard_application_usage.html.

Authors

Giovanni Saraceno, Marianthi Markatou, Raktim Mukhopadhyay, Mojgan Golzy\ Maintainer: Giovanni Saraceno \<gsaracen\@buffalo.edu>

Citation

If you use this package in your research or work, please cite it as follows:

Saraceno, G., Markatou, M., Mukhopadhyay, R. and Golzy, M. (2024). QuadratiK: Collection of Methods Constructed using Kernel-Based Quadratic Distances. https://cran.r-project.org/package=QuadratiK, https://github.com/giovsaraceno/QuadratiK-package, https://giovsaraceno.github.io/QuadratiK-package/.

@Manual{saraceno2024QuadratiK,  
   title = {QuadratiK: Collection of Methods Constructed using Kernel-Based 
            Quadratic Distances},  
   author = {Giovanni Saraceno and Marianthi Markatou and Raktim Mukhopadhyay 
             and Mojgan Golzy},  
   year = {2024},  
   note = {<https://cran.r-project.org/package=QuadratiK>,
            <https://github.com/giovsaraceno/QuadratiK-package>,
            <https://giovsaraceno.github.io/QuadratiK-package/>},  
}

and the associated paper:

Saraceno, G., Markatou, M., Mukhopadhyay, R. and Golzy, M. (2024). Goodness-of-Fit and Clustering of Spherical Data: the QuadratiK package in R and Python. arXiv preprint arXiv:2402.02290v2.

@misc{saraceno2024package, 
      title={Goodness-of-Fit and Clustering of Spherical Data: the QuadratiK 
             package in R and Python},  
      author={Giovanni Saraceno and Marianthi Markatou and Raktim Mukhopadhyay 
              and Mojgan Golzy}, 
      year={2024}, 
      eprint={2402.02290}, 
      archivePrefix={arXiv}, 
      primaryClass={stat.CO}, url={https://arxiv.org/abs/2402.02290}
}

References

Details

The work has been supported by Kaleida Health Foundation and National Science Foundation.



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QuadratiK documentation built on Oct. 29, 2024, 5:08 p.m.