Semantic Scholar Open Access 2013 1009 sitasi

powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions

J. Alstott E. Bullmore D. Plenz

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Abstrak

Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible.

Topik & Kata Kunci

Physics Computer Science Medicine

Penulis (3)

J. Alstott

E. Bullmore

D. Plenz

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Alstott, J., Bullmore, E., Plenz, D. (2013). powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions. https://doi.org/10.1371/journal.pone.0085777

Akses Cepat

Lihat di Sumber doi.org/10.1371/journal.pone.0085777

Informasi Jurnal

Tahun Terbit: 2013
Bahasa: en
Total Sitasi: 1009×
Sumber Database: Semantic Scholar
DOI: 10.1371/journal.pone.0085777
Akses: Open Access ✓