We compare a number of different methods for fitting an ellipse to a static set of measured data points, specifically considering their suitability for interferometric application. We suggest an improved distance approximation for least-square geometric fitting and alternative normalizations for linear algebraic fitting. Of the methods considered, an algebraic fit using a data-dependent normalization has both the least bias in phase and amplitude estimation and the greatest robustness against uneven distribution of data.