Abstract
The first part of the paper is a comparison between the two versions of Tough and Ward's (T/W) model in the generation of surrogate data to a compound stochastic k-distribution prescription. An overview of both versions of the model is presented together with predictor results which allow for direct comparison of the models. The second part of the paper describes the concept of surrogate data testing and introduces a new surrogate data test. The aim is to provide a new statistical hypothesis test which employs the method of surrogate data specifically for sea clutter. The test provides one with a significance measure of how appropriate the k-distribution model of Tough and Ward is for a particular sea clutter data set that is under test. This test incorporates the most recent T/W version 2 model for the generation of its surrogate data. In addition, a new surrogate statistic is introduced which is used to reject/accept the null hypothesis. This statistic is the normalised mean square error (NMSE) from a predictor and is a statistic which can be applied to any type of time-series. An overview of the method is presented together with results for two sea clutter data sets.
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