random.
chisquare
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。
注解
新代码应该使用 chisquare A方法 default_rng() 请参阅 快速启动 .
default_rng()
自由度数必须大于0。
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。
(m, n, k)
m * n * k
None
df
np.array(df).size
从参数化卡方分布中提取样本。
什么时候？ df <=0或当 size （例如） size=-1 ）。
size=-1
参见
Generator.chisquare
应该用于新代码。
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：
卡方分布，表示
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？ 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
NIST“工程统计手册”https://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm
实例
>>> np.random.chisquare(2,4) array([ 1.89920014, 9.00867716, 3.13710533, 5.62318272]) # random