NAME

       plfit - fits power-law distributions to empirical data

SYNOPSIS

       plfit [OPTIONS] [infile ...]

DESCRIPTION

       Reads  data  points  from  each  given  input file and fits a power-law distribution to them, one by one,
       according to the method of Clauset, Shalizi and Newman. If no input files are given, the  standard  input
       will be processed.

       This implementation uses the L-BFGS optimization method to find the optimal alpha for a given xmin in the
       discrete  case.  If  you  want  to  use the legacy brute-force approach originally published in the above
       paper, use the -a switch.

OPTIONS

       -h     shows this help message

       -v     shows version information

       -a RANGE
              use legacy brute-force search for the optimal alpha when  a  discrete  power-law  distribution  is
              fitted.  RANGE must be in MIN:STEP:MAX format, the default is 1.5:0.01:3.5.

       -b     brief (but easily parseable) output format

       -c     force continuous fitting even when every sample is an integer

       -D VALUE
              divide  each  sample  in  the  input  data  by  VALUE  to prevent underflows when fitting discrete
              power-law distribution

       -e EPS try to provide a p-value with a precision of EPS when the p-value is calculated  using  the  exact
              method. The default is 0.01.

       -f     use finite-size correction

       -m XMIN
              use XMIN as the minimum value for x instead of searching for the optimal value

       -M     print  the  first  four  central moments (i.e. mean, variance, skewness and kurtosis) of the input
              data to help assessing the shape of the pdf it may have come from.

       -p METHOD
              use METHOD to calculate the p-value. Must be one of skip, approximate or exact. Default is skip.

       -s SEED
              use SEED to seed the random number generator

plfit                                               July 2021                                           PLFIT(1)