Speaker
Ms
Elke D'Huys
(Royal Observatory of Belgium)
Description
Many natural processes exhibit power law behavior in distributions of measurements such as spatial dimensions and energy content. The exponent of the power law distribution is linked to the underlying physical process and far-reaching conclusions are therefore often derived from its precise value. For example, the enigmatic coronal heating problem is believed to be instantly solved if the power law exponent of the energy content of nanoflares is steeper than 2. Obviously studying power law distributions over several orders of magnitudes requires large amounts of measurements (events) and appropriate methodology. In this presentation we demonstrate the shortcomings of the most popular methods applied to typical sample sizes. We use synthetic data to study the effect of the sample size on the performance of different estimation methods and show that vast amounts of data are needed to obtain a reliable result with graphical methods. We revisit in-house published results on power laws for the angular width of solar Coronal Mass Ejections (CMEs) and the radiative losses of nanoflares. We demonstrate the benefits of the Maximum Likelihood Estimator (MLE) and advocate its use.
Primary author
Ms
Elke D'Huys
(Royal Observatory of Belgium)
