Orlecka-Sikora, Beata and Lasocki, Stanislaw (2005) Nonparametric Characterization of Mining Induced Seismic Sources. In: Controling Seismic Risk RaSiM6. Australian Centre for Geomechanics, Nedlands, Australia, pp. 555-560. ISBN 0-9756756-1-3
Full text not available from this repository.Abstract
Statistical properties of seismicity are expressed by probabilistic distributions of seismic source parameters, out of which the magnitude distribution is the most important in the seismic hazard analysis. Owing to its complexity the magnitude distribution of mining-induced events cannot be accurately represented by any of the known parametric models. Hence, it was recently proposed that a kernel nonparametric estimator be used for this purpose. This paper describes a modified version of this estimator, which adapts to the uneven coverage of the magnitude range with sample data. The probabilistic characterization is incomplete without confidence intervals of the probability function estimates. In order to estimate the confidence intervals for the cumulative distribution function of magnitude we have developed an algorithm based on the bootstrap and jackknife resampling methods. Monte Carlo simulations have shown that this technique provides satisfactory results for a reasonably wide range of sample sizes, regardless the actual shape of the magnitude distribution. We also provide an example of use of the nonparametric interval estimation method for characterizing the seismicity from an underground copper mine in the Legnica-Głogów Copper District in Poland.
| Item Type: | Book Section |
|---|---|
| Subjects: | Region > Poland > Legnica-Glogow Copper District Inducing technology > Underground mining Methodology > Method and procesing |
| Project: | IS-EPOS project > LGCD: Regional seismicity and ground motion associating underground hard rock mining |