We propose a new approach to constructing robust hypothesis tests based on general M-estimators with possibly non-differentiable estimating functions. The proposed test employs a random normalizing matrix computed using only recursive M-estimators to eliminate the nuisance parameters arising...

We propose a class of robust M tests for distribution symmetry of time series data. The proposed tests are robust to the estimation effect of replacing the unknown location parameter with its consistent estimator and are constructed by extending the M tests of Kuan and Lee (2006) and Lee (2007)...