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powerlaw
The frequency-area distribution of forest fires satisfies the powerlaw relation in the critical state.
      
The proper evaluation of powerlaw flow models in three dimensions to backup our inferences is beyond the scope of this study.
      
The only difference is that the use of powerlaw functions in BST is much more general than linear regression.
      
The powerlaw aggregation and exponential fragmentation leads to an obvious asymmetry in the chain size peaks.
      
Up to our knowledge, these are the first cascades which deviate from pure powerlaw scaling.
      
Under these conditions, tree clusters of all sizes are observed, which follow a powerlaw frequency distribution.
      
When n is too small, though, a range of values appears which can then often be tted to a powerlaw if desired.
      
We then perform logarithmic and linear LSE regressions to look for powerlaw relations.
      
We observe that in the range of approximate powerlaw behavior, the slope of the distribution is about !1.3.
      
 

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