Network Global Testing by Counting Graphlets
Authors: Jiashun Jin, Zheng Ke, Shengming Luo
ICML 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We support our methods with careful analysis and numerical study with simulated data and a real data example. 4. Simulations. Experiment 1 (checking for asymptotic normality). Fixing n = 200... 5. Application to a Football Network |
| Researcher Affiliation | Academia | 1Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, USA 2Department of Statistics, University of Chicago, Chicago, USA. |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any information or links regarding open-source code for the described methodology. |
| Open Datasets | Yes | In the college football network (Girvan & Newman, 2002) |
| Dataset Splits | No | The paper describes simulation setups and an application to a real-world network, but it does not specify explicit training, validation, or test dataset splits (e.g., percentages, sample counts, or references to predefined standard splits). |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | Yes | Fixing n = 200, we consider a null setting where θi s are from 10θi iid Pareto(4, 0.375); (note: severe degree heterogeneity!) We also consider an alternative case where θi s are from 2θi iid Pareto(4, 0.375)... Fix (n, K) = (300, 10). All nodes are pure with 30 in each commu-nity. For (a, b) and h > 0, let the matrix P be the same as in Section 3.3. Set θi = (h/ θ ) θi, where θi iid Pareto(4, 0.375); we note that θ = h. Fixing 0 < α < 1, let zα be the (1 α)-quantile of N(0, 1). |