Fit one model | Run several methods | Compare one coefficient | Plot the robust standard errors | Compare confidence intervals directly | Compare covariance objects | Compare diagnostics across methods | What to report

HC inference versus feasible GLS | The multiplicative variance model | Two estimators | Harvey two-step | Maximum likelihood | Data and model | Maximum likelihood fit | Extracting the fit | Custom variance models | Model selection with AIC and BIC | Comparison with HC standard errors | Practical guidance

The model and the target covariance matrix | The sandwich form | The hat matrix and leverage | Residual compression | The classical HC family | HC5 and HC5m | Overshooting | HCbeta motivation | HCbeta construction | Normal Wald inference | Practical guidance | Implementation notes | References

Data and model | Available estimators | Robust inference | Test extraction | Confidence interval extraction | Coefficients and covariance matrices | Covariance-only workflow | Plots | Typical workflow

The method | Data and model | Running the bootstrap | Extractors | Visualizing the intervals | An empirical reference for HC standard errors | Reproducibility | Running in parallel | Practical guidance

Motivation | The algorithm | Consistency | Numerical implementation

Run HCbeta | Inspect HCbeta parameters | Inspect leverage and weights | Run a sensitivity check

Goal | Prepare the data | Fit a classifier | Fit calibrators | Compare calibration metrics | Plot the calibrated probabilities

Why calibration matters | A three-split workflow | Fit a calibrator | Compare methods | Reliability diagram | Cross-validated calibration | Optional reference validation | Current scope

The main decision | Match the input scale | Compare methods on held-out data | Practical guidance

From two classes to several | Simulating an overconfident classifier | Measuring multiclass calibration | Temperature scaling on logits | Dirichlet calibration on probabilities | One-vs-rest calibration | Comparing the calibrators | Reliability diagram | Out-of-fold calibration | Scope

Purpose | Optional checks | Why not compare every method | Running the optional tests

Modified Beta Weibull distribution | Modified Beta Gamma distribution

Understanding the Method | Installation and loading the package | Using the accept_reject Function | Examples | Generating discrete observations | Generating continuous observations | Accessing metadata

Quantile-Quantile Plot | General usage format: | Examples | Discrete case | Continuous case

Motivation | Example of inspection