An asymptotically optimal detector for Gaussianity testing

Problem of testing the Gaussianity of a stationary process where the data can be assumed to be independent and identically distributed is handled with novel approach. Good asymptotical properties can be extrapolated to small sample size and the performance comparison with other classical tests revealed moderate improvement, and this allows the easy calculation of the Bayesian posterior probabilities corresponding to the two classes involved in this problem.