Block Bootstrap for the Empirical Process of Long‐Range Dependent Data

Tewes, Johannes

doi:10.1111/jtsa.12256

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…It is noteworthy that while bootstrap is efficacious in many scenarios, it does possess certain limitations. For instance, if there exists long-term dependencies or correlations among the original data, the bootstrap method might introduce biases (Tewes, 2018). However, in this study, our data consisted of independent observations regarding typhoon storm surge disaster losses, thus the limitations of the method did not significantly impact our research.…”

Section: Expansion Of Training Samplesmentioning

confidence: 97%

Economic loss assessment of typhoon-induced storm surge disasters in the South China Sea based on GSA-BP model

Zhang,

Shen

et al. 2023

Front. Earth Sci.

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In the context of global climate warming and rising sea levels, the frequency of tropical cyclones in the South China Sea region has shown a significant upward trend in recent years. Consequently, the coastal areas of the South China Sea are increasingly vulnerable to storm surge disasters induced by typhoon, posing severe challenges to disaster prevention and mitigation in affected cities. Therefore, establishing a multi-indicator assessment system for typhoon storm surges is crucial to provide scientific references for effective defense measures against disasters in the region. This study examines 25 sets of typhoon storm surge data from the South China Sea spanning the years 1989–2020. A comprehensive assessment system was constructed to evaluate the damages caused by storm surges by incorporating the maximum wind speed of typhoons. To reduce redundancy among multiple indicators in the assessment system and enhance the stability and operational efficiency of the storm surge-induced disaster loss model, the entropy method and bootstrap toolbox were employed to process post-disaster data. Furthermore, the genetic simulated annealing algorithm was utilized to optimize a backpropagation neural network intelligent model (GSA-BP), enabling pre-assessment of the risks associated with storm surge disasters induced by typhoon and related economic losses. The results indicate that the GSA-BP model outperforms the genetic algorithm optimized BP model (GA-BP) and the simulated annealing algorithm-optimized BP model (SA-BP) in terms of predicting direct economic losses caused by storm surges. The GSA-BP model exhibits higher prediction accuracy, shorter computation time, and faster convergence speed. It offers a new approach to predicting storm surge losses in coastal cities along the South China Sea.

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Section: Expansion Of Training Samplesmentioning

confidence: 97%

Economic loss assessment of typhoon-induced storm surge disasters in the South China Sea based on GSA-BP model

Zhang,

Shen

et al. 2023

Front. Earth Sci.

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“…Menendez et al, 2013). Moreover, tests of the null hypothesis that m is one are available in the literature (Beran et al, 2016;Tewes, 2018).…”

Section: Data Examplementioning

confidence: 99%

Estimating the Mean Direction of Strongly Dependent Circular Time Series

Beran

Ghosh

2019

Journal Time Series Analysis

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A class of circular processes based on Gaussian subordination is introduced. This allows for flexible modelling of directional time series with long‐range dependence. Based on limit theorems for subordinated processes and consistent estimation of nuisance parameters, asymptotic confidence intervals for the mean direction are derived. Extensions to cases where the direction depends on explanatory variables are also considered. Simulations and a data example illustrate the proposed method.

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“…In practical applications this might be not the case. Solutions are self-normalization (Shao (2011)), estimating the the Hurst-coefficient (see for example Künsch (1987)) and bootstrap estimators for J m (x) (Tewes (2016)).…”

Section: Asymptotic Behavior Of the Change-point Statisticsmentioning

confidence: 99%

Change-point tests under local alternatives for long-range dependent processes

Tewes¹

2017

Electron. J. Statist.

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We consider the change-point problem for the marginal distribution of subordinated Gaussian processes that exhibit long-range dependence. The asymptotic distributions of Kolmogorov-Smirnov-and Cramér-von Mises type statistics are investigated under local alternatives. By doing so we are able to compute the asymptotic relative efficiency of the mentioned tests and the CUSUM test. In the special case of a mean-shift in Gaussian data it is always 1. Moreover our theory covers the scenario where the Hermite rank of the underlying process changes.In a small simulation study we show that the theoretical findings carry over to the finite sample performance of the tests..Keywords: asymptotic relative efficiency, change-point test, empirical process, local alternatives, long-range dependence.where the convergence takes place in D([0, 1] × [−∞, ∞]), equipped with the uniform topology.and (Z m,H (t)) t∈[0,1] is an m-th order Hermite process, see Taqqu (1979) for a definition.Remark 2.1. In the case m = 1, the Hermite process becomes the well known fractional Brownian Motion, which we denote by B H (t).

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Block Bootstrap for the Empirical Process of Long‐Range Dependent Data

Cited by 5 publications

References 35 publications

Economic loss assessment of typhoon-induced storm surge disasters in the South China Sea based on GSA-BP model

Economic loss assessment of typhoon-induced storm surge disasters in the South China Sea based on GSA-BP model

Estimating the Mean Direction of Strongly Dependent Circular Time Series

Change-point tests under local alternatives for long-range dependent processes

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