Modified score functions for von Mises regressions

We derive and evaluate a novel estimation approach for the von Mises regression model based on a modified score function whose solution ensures an estimator with a smaller asymptotic bias than the original maximum likelihood estimator. We consider Monte Carlo simulation experiments to show that the new estimation approach yields nearly unbiased estimates. An application to real data is also considered for illustrative purposes.