Simulation Data for Communication-Efficient Estimation with Non-Random and Missing Data

Simulation code and supplementary materials for a 2026 paper on distributed estimation methods. Xirui Liu authored this research, which proposes two CPOU methods for handling non-randomly distributed and incomplete data across local machines. The 248.4 KB archive includes R code, PDF documentation, and text files to replicate the study's empirical results.

Use Cases

• Benchmarking distributed estimators based on the described CPOU methods against traditional approaches
• Studying the impact of non-random data distribution on statistical efficiency using the provided simulation framework
• Testing bias reduction techniques for missing data based on the inverse probability weighting (IPW) implementation
• Evaluating one-step updating procedures for improving estimator efficiency in distributed settings

Strengths

• Includes full simulation code in R for method replication
• Supplementary materials are provided online as referenced in the description
• Released under a permissive CC-BY-4.0 license

Limitations

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

Provenance

Source

Xirui Liu via figshare

Collection Method

Likely generated for simulation studies in the associated research paper.

Freshness

Last updated 2026-06-03 11:01:40; freshness should be verified