Nonuniformity of P-values Can Occur Early in Diverging Dimensions
Authors: Yingying Fan, Emre Demirkaya, Jinchi Lv
JMLR 2019 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our theoretical characterizations are confirmed by simulation studies. ... Section 4 presents several simulation examples verifying the theoretical phenomenon. |
| Researcher Affiliation | Academia | Yingying Fan EMAIL Data Sciences and Operations Department University of Southern California Los Angeles, CA 90089, USA; Emre Demirkaya EMAIL Business Analytics & Statistics The University of Tennessee, Knoxville Knoxville, TN 37996-4140, USA; Jinchi Lv EMAIL Data Sciences and Operations Department University of Southern California Los Angeles, CA 90089, USA |
| Pseudocode | No | The paper describes theoretical proofs and derivations. There are no explicit pseudocode or algorithm blocks presented. |
| Open Source Code | No | The paper does not contain any statements or links indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper uses simulated data for its numerical studies, as indicated by "we generate the n p design matrix X" and "each yi has Bernoulli distribution". It does not refer to any external, publicly available datasets. |
| Dataset Splits | No | The numerical studies involve generating synthetic data based on specified distributions and parameters, rather than using pre-existing datasets with defined train/test/validation splits. Therefore, dataset split information is not applicable in the traditional sense for this paper's methodology. |
| Hardware Specification | No | The paper describes simulation experiments but does not provide any specific details about the hardware (e.g., GPU, CPU models, memory) used to run these simulations. |
| Software Dependencies | No | The paper does not mention any specific software or library names with version numbers that were used for the simulations or analyses. |
| Experiment Setup | Yes | To examine the asymptotic results we set the sample size n = 1000. In each example, we consider a spectrum of dimensionality p with varying rate of growth with sample size n. ... We set p = [nα0] with α0 in the grid {2/3 4δ, ..., 2/3 + 4δ, (log(n) log(2))/ log(n)} for δ = 0.05. For example 3, we pick s signals uniformly at random among all but the first components, where a random half of them are chosen as 3 and the other half are set as 3. |