MCMC Diagnostic Statistics for Phenotype Regression Coefficients

A summary of Markov Chain Monte Carlo (MCMC) diagnostics for regression coefficients of phenotypes. The dataset contains Gelman-Rubin and Effective Sample Size (ESS) statistics, likely derived from a Bayesian analysis of genetic or crop data. It is a 5.5 KB Excel file authored by Rupam Basu and last updated in March 2026.

Use Cases

• Assessing MCMC convergence for phenotype regression models based on the provided Gelman-Rubin statistics.
• Evaluating sampling efficiency in Bayesian analyses based on the reported Effective Sample Size (ESS) values.
• Benchmarking computational performance of Bayesian modeling approaches for genetic data.
• Validating statistical models in genome-wide association studies (GWAS) based on the diagnostic metrics.

Strengths

• File size is 5.5 KB, indicating a compact and focused summary.
• Released under a permissive CC-BY-4.0 license.
• Last update timestamp is precise (2026-03-17 17:51:04).

Limitations

• Row count and specific column definitions are unknown.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Rupam Basu.

Collection Method

Likely generated as output from a Bayesian statistical analysis.

Time Range

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Freshness

Last updated 2026-03-17 17:51:04; freshness should be verified.

Geography

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