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Multifractal estimation using a standard box-counting algorithm

Authors: Leonardo A. Saravia;

Multifractal estimation using a standard box-counting algorithm

Abstract

Software used to determine multifractal spectra: Generalized dimensions Dq and spectrum of singularities f(alfa), the software was used in the paper: Saravia LA, Giorgi A, Momo F (2012) Multifractal growth in periphyton communities. Oikos 121: 1810–1820. mfSBA estimate both spectra and outputs data to evaluate the fits. A more detailed description is in the file mfSBA_README. mfSBArnz estimate the Dq spectrun and randomize the original image N times to calculate a confidence interval to test the hipothesis that the original distribution was random. multiSpeciesSBA estimates the multifractal spectra of a 2D species distribution assuming that each position is one individual and that each value represents a different specie. sed2grad transforms a sed file using a discrete gradient transformation. This program was used in the paper: Saravia LA, Giorgi A, Momo FR (2012) Multifractal Spatial Patterns and Diversity in an Ecological Succession. PLoS One 7: e34096. The programs accept as input tiff, and sed files (ASCII format). b4-991008bio.sed/tif are examples from the paper of 2D biomass distributions to analyze with the program. q21.sed is a file with q values used to estimate spectra. Please leave an Issue on github if you have some trouble.

Please be aware that this code is not being actively developed, as it is an archive of the code as it was at the time of publication in the associated F1000Research article. For the latest version of this code, please see https://github.com/lsaravia/mfsba.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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