https://github.com/mamba413/nonparametric-statistical-inference-via-metric-distribution-function-in-metric-spaces

Reproducible materials for Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces (JASA, 2023+)
https://github.com/mamba413/nonparametric-statistical-inference-via-metric-distribution-function-in-metric-spaces

distribution-function empirical-distributions metric-spaces non-parametric-statistics

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Reproducible materials for Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces (JASA, 2023+)

• Host: GitHub
• URL: https://github.com/mamba413/nonparametric-statistical-inference-via-metric-distribution-function-in-metric-spaces
• Owner: Mamba413
• Created: 2023-10-21T16:18:41.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-17T11:33:32.000Z (12 months ago)
• Last Synced: 2023-11-18T11:45:01.770Z (12 months ago)
• Topics: distribution-function, empirical-distributions, metric-spaces, non-parametric-statistics
• Language: R
• Homepage: https://www.tandfonline.com/doi/full/10.1080/01621459.2023.2277417
• Size: 3.22 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Reproducible materials

This repository contains scripts to run the simulation described in [Nonparametric Statistical Inference via Metric Distribution Function in Metric Spaces](https://arxiv.org/abs/2107.07317). 

![](real_theory_bridge.png)

## Software

Please install `Ball` 1.3.13 to use the tests mentioned in the paper. 

> Note: download this package from [here](https://github.com/Mamba413/Nonparametric-Statistical-Inference-via-Metric-Distribution-Function-in-Metric-Spaces/blob/main/Ball_1.3.13.tar.gz). Some advanced features haven't been integrated into the `Ball` package (version 1.3.13) in R CRAN. We expect to make the `Ball` package on R CRAN support these new features in version 1.3.14.

## Reproducible code

We have organized our scripts to improve the reproducibility of experiments. Specifically, each R script file corresponds to a certain part of the results in the paper, which are listed below:

- `large_homogeneity_n.R` <-> Results in Figure 3A

- `large_joint_independence_n.R` <-> Results in Figure 3B

- `compare_homo_methods.R` <-> Results in Figure 4A

- `compare_indep_methods.R` <-> Results in Figure 4B

- `real_data_adni_analysis.R` <-> Results in Table 1

- `real_data_adhd200_analysis.R` <-> Results in Table 2

Notice that, before conducting these scripts, please modify the your_path in each script accordingly. 

## Citations

Please cite the following publications if you make use of the material here.

- Xueqin Wang, Jin Zhu, Wenliang Pan, Junzhu Zhu, and Heping Zhang (JASA, 2023+). Nonparametric statistical inference via metric distribution function in metric spaces. arXiv preprint arXiv:2107.07317.

The corresponding BibteX entries:

```

@article{wang2023nonparametric,

  title={Nonparametric statistical inference via metric distribution function in metric spaces},

  author={Wang, Xueqin and Zhu, Jin and Pan, Wenliang and Zhu, Junhao and Zhang, Heping},

  journal={Journal of American Statistical Association},

  year={2023+},

  doi={10.1080/01621459.2023.2277417},

}

```

## Contact

Please direct questions and comments to the [issues page](https://github.com/Mamba413/Nonparametric-Statistical-Inference-via-Metric-Distribution-Function-in-Metric-Spaces/issues).