High-Dimensional Statistical Inference and Variable Selection Simulation Results

675.8 KB of simulation results and supporting code for a proposed sufficient dimension association (SDA) method for high-dimensional data analysis. The dataset, authored by Shangyuan Ye and last updated in April 2026, includes a demonstration using gene expression data from the Alzheimer Disease Neuroimaging Initiative. Supplementary materials for reproducing the work are available.

Use Cases

• Benchmarking variable selection methods against the proposed SDA technique based on simulation results
• Testing statistical inference procedures for high-dimensional data under model misspecification
• Reproducing the analysis of Alzheimer's Disease gene expression data mentioned in the description

Strengths

• Includes 675.8 KB of simulation code and results for method validation
• Provides supplementary materials for full reproducibility of the research work
• Dataset is openly licensed under CC-BY-4.0

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

Shangyuan Ye via figshare

Collection Method

Likely contains results from simulation studies and analysis of the Alzheimer Disease Neuroimaging Initiative (ADNI) gene expression data.

Freshness

Last updated 2026-04-28 19:47:39; freshness should be verified