Minimax Nonparametric Parallelism Test
Authors: Xin Xing, Meimei Liu, Ping Ma, Wenxuan Zhong
JMLR 2020 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Simulation studies are conducted to investigate the empirical performance of the proposed test. DNA methylation and neuroimaging studies are presented to illustrate potential applications of the test. |
| Researcher Affiliation | Academia | Department of Statistics Virginia Tech, Blacksburg, VA, 24061, USA; Department of Statistics University of Georgia, Athens, GA 30601, USA |
| Pseudocode | No | The paper describes the methodology using mathematical derivations and prose, but does not include any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | The software is available at https://github.com/BioAlgs/Parallelism . |
| Open Datasets | Yes | Recently, Filarsky et al. (2016) reported a DNA methylation study for chronic lymphocytic leukemia (CLL) patients. ... Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). |
| Dataset Splits | No | The paper describes data generation for simulation studies and patient groups for real-world applications but does not specify training, testing, or validation dataset splits for its experiments. |
| Hardware Specification | Yes | We conducted the comparison on a computer workstation with core Intel i7 8700k CPU and 32 Gb RAM. |
| Software Dependencies | No | The paper mentions the availability of its own software and refers to 'f MRI Expert Analysis Tool (FEAT) (Smith et al., 2004)' but does not provide specific version numbers for any software dependencies. |
| Experiment Setup | Yes | In all four examples, we generated 100 to 1000 observations with an increment of 100 observations in each simulation for both case and control groups in Equation (1), where x1i iid U(0, 1) and ϵij iid N(0, 1). Each example was repeated 500 times for power and other comparisons. ... We set the significance level as 0.05 and repeated 500 times for evaluating the empirical size and power. ... Through controlling FDR < 0.01 using Benjamini-Hochberg procedure (Benjamini and Hochberg, 1995). |