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Volcanic eruptions are commonly characterized by time series of events, such as earthquakes and explosions, which can be analysed by statistical techniques to interpret physical mechanisms of eruption and to be applied to forecasting. We apply geostatistical methods (Chiles & Delfiner 1999) to a time series of Vulcanian explosions that occurred at the Soufriére Hills volcano, Montserrat (Fig. 1) in the period 22 September to 21 October 1997. These techniques can be used to detect correlations in occurrences of volcanic processes. Such correlations indicate that the processes are capable of remembering their past activities and can be used to detect memory effects in dynamic systems.

The sequence of 75 Vulcanian explosions at Soufriére Hills followed a collapse of the andesite lava dome on 21 September 1997 (Druitt et al. 2002). The mean repose interval was 9.6 h with a minimum of 2.8 h and a maximum of 33.7 h (Connor et al. 2003). The explosions were shortlived (tens of seconds), impulsive and energetic (Druitt et al. 2002) with column heights between 5 and 15 km above sea level and individual ejecta volumes up to 6.6 x 105m3. The explosion time series is complete and precisely timed by seismic signals, allowing us to apply a stochastic approach using the variogram (Chiles & Delfiner 1999; Jaquet & Carniel 2001) to characterize the statistical behaviour. The data consist of the date and time of an explosion (Tm), the time interval

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