class documentation

`class FittedPowerLaw:`

Result of fitting a power-law to a vector of samples

Example:

>>> result = power_law_fit([1, 2, 3, 4, 5, 6]) >>> result # doctest:+ELLIPSIS FittedPowerLaw(continuous=False, alpha=2.42..., xmin=3.0, L=-7.54..., D=0.21..., p=0.993...) >>> print(result) # doctest:+ELLIPSIS Fitted power-law distribution on discrete data <BLANKLINE> Exponent (alpha) = 2.42... Cutoff (xmin) = 3.000000 <BLANKLINE> Log-likelihood = -7.54... <BLANKLINE> H0: data was drawn from the fitted distribution <BLANKLINE> KS test statistic = 0.21... p-value = 0.993... <BLANKLINE> H0 could not be rejected at significance level 0.05 >>> result.alpha # doctest:+ELLIPSIS 2.42... >>> result.xmin 3.0 >>> result.continuous False

Method | `__init__` |
Undocumented |

Method | `__repr__` |
Undocumented |

Method | `__str__` |
Undocumented |

Method | `summary` |
Returns the summary of the power law fit. |

Instance Variable | `alpha` |
Undocumented |

Instance Variable | `continuous` |
Undocumented |

Instance Variable | `D` |
Undocumented |

Instance Variable | `L` |
Undocumented |

Instance Variable | `p` |
Undocumented |

Instance Variable | `xmin` |
Undocumented |