easystats/performance

Health v2 · maintenance only

Adoption not part of the score

1151 stars · 108 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An R package from the easystats ecosystem that computes indices of model quality and goodness of fit, such as R-squared, RMSE, ICC, AIC, and LOO. It also provides checks for overdispersion, zero-inflation, convergence, and singularity in (mixed) regression models.

Use cases

• compute r-squared for a regression model in R
• calculate intraclass correlation coefficient for a mixed model
• compare model fit with AIC and LOO
• check a mixed model for overdispersion and zero-inflation
• assess convergence and singularity of a lme4 model
• get RMSE and fit indices for a statistical model
• evaluate goodness of fit across different model types

When to choose

• you fit regression or mixed models in R and need consistent fit indices
• you want a unified interface for model quality metrics across many model classes
• you use the easystats ecosystem and want integrated model diagnostics

When to avoid

• you work outside R or need deep-learning-specific benchmarking
• you need a general-purpose ML evaluation framework like scikit-learn metrics
• you only need simple descriptive statistics rather than model fit assessment

Facets

library · maturity active

testing benchmarking data-science data-science machine-learning developer-tools python r-package model-quality goodness-of-fit mixed-models regression easystats cran statistics

Member repositories

For agents

markdown · JSON · MCP: product_card(name="easystats/performance")