tokens: one. The choice of S depends on the sampling strategy, and we recommend a fine scanning of the complete velocity spectrum which corresponds to S = 1 and would be covered by 1 + N − R bins. Then, we calculate the median for the spatial coordinates as well as for the radial velocity for each data bin. Median, as a central value estimator, is more robust than mean against the presence of outliers, and we expect to find some points away from the central value in most cases. A robust estimator of the standard deviation is given by: (see Gott et al. 2001 , for a detailed discussion of median statistics), where MAD is the median of the absolute deviations from the data median. The error of this central value can then be approached as . The b parameter is dependent on the distribution function underlying the data. In the following we will take b = 1.4826 as default. The next step is to obtain the MST graph for the R objects in each bin. The median of the edge length distribution is the first indicator of the group compactness (equation 2 ). As discussed by Maschberger Clarke ( 2011 ), median is the best estimator of the central value of the edge length when we could be facing a clumpy distribution for a given velocity range. The same is applied to a set of R randomly extracted objects from the complete sample. We repeat this step 500 times and calculate the mean and the standard deviation of the 500 medians. We chose 500 repetitions to get a reliable average of the edge length median for the R sized random sample, as recommended by Allison et al. ( 2009 ). This way we estimate the edge length median of the MST for a reference set of R objects, representing the whole sample. Then we estimate the kinematic segregation index, , as where j is the bin identification and i is the order of the first element in the bin, both being connected through the relation i = 1 + ( j − 1) × S . Supra-index 500 indicates that the average is calculated over 500 stochastic realizations. The total number of bins is given by the integer part of 1 + (( N − R )/ S ). A plot of versus the median of the radial velocity in the RV j interval for all j , shows what we name the spectrum of kinematic groupings which provides an interesting and useful tool for the exploratory analysis of the stellar system phase space. Those that verify the inequality mark the radial velocity channels, RV j , where a kinematic segregation has been detected. Here, we decided to multiply by two the standard deviation term as a conservative criterion in the detection of groupings (confidence level greater than 95 per cent). Note that is not the median of the 500 standard deviations but the standard deviation of the 500 medians. Figure 1. Schematic representation of the six test cases. From top to bottom and from left to right they are: (1) two spatially separated clusters with the same central velocity of 1 km s −1 ; (2) two clusters separated both in space and in velocity, where the mean velocities
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