类文档
将幂律拟合到样本向量的结果
示例
>>> 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
| 方法 | __init__ |
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| 方法 | __repr__ |
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| 方法 | __str__ |
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| 方法 | summary |
返回幂律拟合的摘要。 |
| 实例变量 | alpha |
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| 实例变量 | continuous |
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| 实例变量 | D |
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| 实例变量 | L |
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| 实例变量 | p |
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| 实例变量 | xmin |
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