numpy.random.Generator.chisquare¶

方法

random.Generator.chisquare(df, size=None)¶

从卡方分布中提取样本。

什么时候？ df 独立随机变量，每一个都有标准正态分布（平均值0，方差1），是平方和总和，得到的分布是卡方分布（见注释）。这种分布通常用于假设检验。

参数

df浮点数或类似浮点数的数组: 自由度数必须大于0。
sizeint或int的元组，可选: 输出形状。如果给定的形状是，例如， (m, n, k) 然后 m * n * k 取样。如果尺寸是 None （默认），如果 df 是标量。否则， np.array(df).size 取样。

返回

outndarray或scalar: 从参数化卡方分布中提取样本。

加薪

ValueError: 什么时候？ df <=0或当 size （例如） size=-1 ）。

笔记

通过平方和得到的变量 df 独立的标准正态分布随机变量：

$Q=\sum_i=0 ^ \mathtt df x^2_i$

卡方分布，表示

$Q \sim \chi^2_k.$

卡方分布的概率密度函数是

System Message: WARNING/2 (p（x）=\frac{（1/2）^{k/2}}{\Gamma（k/2）})

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在哪里？ $\Gamma$ 是伽玛函数，

System Message: WARNING/2 (\伽玛（x）=\int-\infty t x-1 e-t dt.)

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工具书类

1: NIST“工程统计手册”https://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm

实例

>>> np.random.default_rng().chisquare(2,4)
array([ 1.89920014,  9.00867716,  3.13710533,  5.62318272]) # random

numpy.random.Generator.binomial numpy.random.Generator.dirichlet