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How to make a Hill plot

如何绘制 Hill 图

An abundance of high quality data sets requiring heavy tailed models necessitates reliable methods of estimating the shape parameter governing the degree of tail heaviness. The Hill estimator is a popular method for doing this but its practical use is encumbered by several difficulties. We show that an alternative method of plotting Hill estimator values is more revealing than the standard method unless the underlying data comes from a Pareto distribution.

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Limit Theory for the Sample Covariance and Correlation Functions of Moving Averages

移动平均过程样本协方差与相关函数的极限理论

Let $X_t = \sum^\infty_{j=-\infty} c_jZ_{t-j}$ be a moving average process where the $Z_t$'s are iid and have regularly varying tail probabilities with index $\alpha > 0$. The limit distribution of the sample covariance function is derived in the case that the process has a finite variance but an infinite fourth moment. Furthermore, in the infinite variance case $(0 < \alpha < 2)$, the sample correlation function is shown to converge in distribution to the ratio of two…

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Statistical Analysis of Counting Processes.

计数过程的统计分析

1. One-Dimensional Counting Processes.- 1.1. Probabilities on (0,?].- 1.2. The definition of one-dimensional counting processes.- 1.3. Construction of canonical counting processes.- 1.4. Intensities for canonical counting processes.- 1.5. Martingale decompositions for canonical counting processes.- 1.6. Statistical models and likelihood ratios.- Notes.- Exercises.- 2. Multivariate Counting Processes.- 2.1. Definition and construction of multivariate counting processes.- 2.2.…

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Tail Estimates Motivated by Extreme Value Theory

极值理论启发的分布上尾估计

An estimate of the upper tail of a distribution function which is based on the upper $m$ order statistics from a sample of size $n(m \rightarrow \infty, m/n \rightarrow 0$ as $n \rightarrow \infty)$ is shown to be consistent for a wide class of distribution functions. The empirical mean residual life of the $\log$ transformed data and the sample $1 - m/n$ quantile play a key role in the estimate. The joint asymptotic behavior of the empirical mean residual life and sample $1 - m/n$…

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