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Regression
- Ordinary, constrained, instrumental variables, censored, and errors in variables
- Influence statistics and fit diagnostics
- Ramsey regression specification-error test for omitted variables
- Variance-inflation factors
- Cook’s distance
- COVRATIO
- DFBETAs
- DFITs
- Diagonal elements of hat matrix
- Residuals, standardized residuals, studentized residuals
- Standard errors of the forecast, prediction, and residuals
- Welsch distance
- tests for heteroskedasticity
- Cook and Weisberg test (updated)
- Szroetzer’s rank test
- Information matrix test
- Cameron and Trivedi’s decomposition
- White’s test
- Tests for autocorrelation
- Durbin–Watson
- Durbin–Watson h statistic
- Breusch–Godfrey
- ARCH LM test
- Diagnostic plots
- Added variable (leverage) plot
- Component plus residual plot
- Leverage vs. squared residual plot
- Residual vs. fitted plot
- Residual vs. predictor
- Nested logit models
- Fixed- and random-effects models for panel data
- Traditional, robust (Huber/White/sandwich), cluster-robust, bootstrap,
or jackknife standard errors
- Robust regression
- Graph estimates and confidence intervals
- Newey–West estimator of variance
- Variance-weighted least squares
- GLM
- GLS for cross-sectional time-series data
- List estimates and confidence intervals
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Simultaneous systems
- Three-stage least-squares regression
- Two-stage least-squares regression
- LIML estimation
- GMM estimation
- Tests of instrumental relevance
- Tests of overidentifying restrictions
- Linear constraints within and across equations
- Accepts time-series operators
- Models with selection
Seemingly unrelated regressions
- Linear constraints within and across equations
- Accepts time-series operators
Fractional polynomial regression
- Mean adjustment to variables
- Component+residual plots
Quantile regression
- Median regression
- Least absolute deviations (LAD)
- Regression of any quantile
- Koenker and Bassett or bootstrapped standard errors
Linear mixed models
- Multilevel random effects
- BLUP estimation
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