In theory, earthquake magnitudes follow an exponential distribution. In practice, however, earthquake catalogs report magnitudes with finite resolution, resulting in a discrete (geometric) distribution. To determine the lowest magnitude above which seismic events are completely recorded, the Lilliefors test is commonly applied. Because this test assumes continuous data, it is standard practice to add uniform noise to binned magnitudes prior to testing exponentiality. This work shows analytically that uniform dithering cannot recover the exponential distribution from its geometric form. It instead returns a piecewise-constant residual lifetime distribution, whose deviation from the exponential model becomes detectable as catalog size or bin width increases. Numerical experiments confirm that this deviation yields an overestimation of the magnitude of completeness in large catalogs. We therefore derive the exact noise distribution - a truncated exponential on the bin interval - that correctly restores the continuous exponential distribution over the whole magnitude range. Numerical tests show that this correction yields Lilliefors rejection rates consistent with the significance level for all bin widths and catalog sizes. The proposed solution eliminates a methodological bias in completeness estimation, which especially impacts high-resolution catalogs.
翻译:理论上,地震震级服从指数分布。然而在实际应用中,地震目录报告的震级具有有限分辨率,导致其呈现离散(几何)分布。为确定地震事件被完整记录的最低震级,通常采用Lilliefors检验。由于该检验假设数据连续,标准做法是在检验指数性前向分档震级添加均匀噪声。本文通过解析证明,均匀抖动无法从几何形式恢复指数分布,反而会得到分段恒定的剩余寿命分布,其与指数模型的偏差会随目录规模或分档宽度的增加而变得可检测。数值实验证实,这种偏差会导致在大规模目录中高估完整性震级。因此,我们推导出精确的噪声分布——在分档区间上的截断指数分布——该分布能在整个震级范围内正确恢复连续指数分布。数值测试表明,经此校正后,Lilliefors检验的拒绝率与所有分档宽度和目录规模下的显著性水平保持一致。所提出的解决方案消除了完整性估计中的方法学偏差,该偏差对高分辨率地震目录的影响尤为显著。