Troubleshooting Common Issues

Common Error Messages and Solutions

"Auxiliary regression failed"

Cause: Perfect multicollinearity in auxiliary regression Solution: Check for duplicated or linearly dependent predictors in the auxiliary regression. Removing or combining offending variables usually resolves the issue.

"Log of negative values"

Cause: Negative values in variable used for log transformation Solution: Ensure the variable is strictly positive before applying a log transformation or add a small constant to shift the data.

Performance Issues

Large Datasets

For very large data sets consider using performWhiteTestStreaming() or running diagnostics on a representative sample to reduce computation time.

Convergence Problems

Numerical issues may arise with extreme multicollinearity or poorly scaled variables. Rescaling predictors or using robust optimisation methods can help.

Interpretation Guidelines

When Tests Disagree

No single test is uniformly most powerful. Examine residual plots and consider the nature of your data when diagnostics give conflicting results.

Power Considerations

Some tests have low power in small samples. Simulation via simulate_power() can help determine the best approach for a given situation.