On the goodness-of-fit procedure for normality based on the empirical characteristic function for ranked set sampling data

The behaviour of the goodness-of-fit procedure for normality based on weighted integrals of the empirical characteristic function, discussed in the case of i.i.d. data, for instance, in Epps and Pulley (Biometrika 70:723–726, <CitationRef CitationID="CR7">1983</CitationRef>), is considered here in the context of ranked set sampling (RSS) data. In the RSS context, we obtain the limiting distribution of the empirical characteristic process and perform a power study, against a broad set of alternatives, that enables an evaluation of the gain in power that occurs when a simple random sample is replaced by RSS data. The adaptation of the results obtained in the Gaussian RSS setting to the case of other important location-scale families is also discussed. Copyright Springer-Verlag 2013