Statistical power estimation in Extreme Value Theory

Published: 29 Jan 2018 | Version 1 | DOI: 10.17632/hh2byrbbmf.1
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Description of this data

These files contain the code (three executables in total) and the results carried out by that code. It provides the statistical power analysis and its sensitivity for Kolmogorov-Smirnov (KS), Anderson-Darling (AD) and the Modified Anderson-Darling (MAD) tests for Extreme Value (EV) distributions. The power is estimated via a Monte Carlo approach with 10^9 samples, under "case 0" conditions. The tests were performed varying the reference distribution, the sampling distribution, the sample size and the critical value. The sensitivity analysis was performed on the shape parameter of EV distribution.

Experiment data files

Latest version

  • Version 1

    2018-01-29

    Published: 2018-01-29

    DOI: 10.17632/hh2byrbbmf.1

    Cite this dataset

    Reghenzani, Federico; Massari, Giuseppe; Fornaciari, William (2018), “Statistical power estimation in Extreme Value Theory”, Mendeley Data, v1 http://dx.doi.org/10.17632/hh2byrbbmf.1

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Institutions

Politecnico di Milano Dipartimento di Elettronica Informazione e Bioingegneria

Categories

Real-Time Systems, Statistical Hypothesis Testing, Extreme Value Theory

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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