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Statistical description of non-Gaussian samples in the F2 layer of the ionosphere during heliogeophysical disturbances

机译:在起重Gysicalicalisical扰动期间,在电离层F2层中的非高斯样品的统计描述

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摘要

An adequate statistical method should be developed in order to predict probabilistically the range of ionospheric parameters. This problem is solved in this paper. The time series of the critical frequency of the layer F2-foF2(t) were subjected to statistical processing. For the obtained samples {delta foF2}, statistical distributions and invariants up to the fourth order are calculated. The analysis shows that the distributions differ from the Gaussian law during the disturbances. At levels of sufficiently small probability distributions, there are arbitrarily large deviations from the model of the normal process. Therefore, it is attempted to describe statistical samples {delta foF2} based on the Poisson model. For the studied samples, the exponential characteristic function is selected under the assumption that time series are a superposition of some deterministic and random processes. Using the Fourier transform, the characteristic function is transformed into a nonholomorphic excessive-asymmetric probability-density function. The statistical distributions of the samples {delta foF2} calculated for the disturbed periods are compared with the obtained model distribution function. According to the Kolmogorov's criterion, the probabilities of the coincidence of a posteriori distributions with the theoretical ones are P similar to 0.7-0.9. The conducted analysis makes it possible to draw a conclusion about the applicability of a model based on the Poisson random process for the statistical description and probabilistic variation estimates during heliogeophysical disturbances of the variations {delta foF2}.
机译:应该开发足够的统计方法,以便预测电离层参数的概率。本文解决了这个问题。对层F2-FOF2(T)的临界频率的时间序列进行统计处理。对于获得的样本{Delta Fof2},计算统计分布和不变量,最高为四个顺序。分析表明,分布在干扰期间的高斯法律不同。在足够小的概率分布的级别下,与正常过程的模型有任意大的偏差。因此,基于泊松模型,试图描述统计样本{delta fof2}。对于研究的样本,在假设时间序列是一些确定性和随机过程的叠加的假设下选择指数特征功能。使用傅里叶变换,特性函数被转换为非向量过度不对称的概率密度函数。将对受干扰的时段计算的样品{ΔFOF2}的统计分布与获得的模型分布函数进行比较。根据Kolmogorov的标准,与理论上的后验分布的重合的概率是类似于0.7-0.9的p。进行的分析使得可以基于泊松随机过程基于统计描述和概率变化估计的模型的适用性得出结论,并且在变型的旋转次数{delta fof2}的旋转果性干扰期间。

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