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Modeling Astronomical Time Series with Stochastic Differential Equations

机译:用随机微分方程建模天文时间序列

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A serious limit of many methodologies of data analysis used in astronomical applications is that they are based on statistical techniques developed for predictive and/or exploratory purposes. In many situations, this makes difficult to establish a meaningful link between experimental data and theoretical models. Only techniques of data analysis developed in a specific physical context can be expected to provide useful results. This is especially true for the analysis of the light curves where many techniques have been directly "imported" from Statistics often with unsatisfactory, if not insignificant, results. Here, we show that the methodologies of analysis developed in the context of the Stochastic Dynamics appear much more useful and, in particular, that modeling the experimental time series by means of the stochastic differential equations (SDE) represents a valuable tool of analysis.
机译:在天文应用中使用的许多数据分析方法的严重限制是它们基于为预测和/或探索目的而开发的统计技术。在许多情况下,这使得难以在实验数据和理论模型之间建立有意义的联系。只有在特定物理上下文中开发的数据分析的才能提供有用的结果。这对于分析光明曲线尤其如此,其中许多技术直接从统计数据直接“导入”统计数据,如果不是不足,结果。在这里,我们表明,在随机动力学的上下文中开发的分析方法看起来更有用,特别是通过随机微分方程(SDE)模拟实验时间序列的模拟代表了有价值的分析工具。

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