gvlma is an R package for the global validation of linear model assumptions, authored by Edsel A. Pena and Elizabeth H. Slate. The dataset likely contains statistical test results and diagnostic metrics for assessing model fit. It is sourced from the paperswithcode platform, which aggregates resources for the computer science and mathematics communities.
Use Cases
- Automated diagnostic testing for linear regression assumptions (inferred from domain, verify after download)
- Benchmarking statistical model validation methods (inferred from domain, verify after download)
- Educational tool for teaching regression diagnostics (inferred from domain, verify after download)
Strengths
- Published on the paperswithcode platform, which aggregates peer-reviewed resources.
- Authored by established researchers in statistics.
Limitations
- Metadata is minimal; actual content requires verification after download.
- Row count, file formats, and column definitions are unknown.
- Last update date is unknown; freshness unverified.
Provenance
- Source
- paperswithcode
- Collection Method
- Likely an R software package or associated benchmark data.
- Time Range
- null
- Freshness
- Last updated date is unknown.
- Geography
- null