方法
random.Generator.
logistic
从物流配送中抽取样本。
从具有指定参数、loc（位置或平均值，也包括中位数）和scale（>0）的逻辑分布中提取样本。
分布的参数。默认值为0。
分布的参数。必须为非负。默认值为1。
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 loc 和 scale 都是标量。否则， np.broadcast(loc, scale).size 取样。
(m, n, k)
m * n * k
None
loc
scale
np.broadcast(loc, scale).size
从参数化物流分布中提取样本。
参见
scipy.stats.logistic
概率密度函数、分布或累积密度函数等。
笔记
逻辑分布的概率密度是
System Message: WARNING/2 (p（x）=p（x）=\frac e^-（x-\mu）/s s（1+e^-（x-\mu）/s）^2，)
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Package inputenc Error: Unicode character ） (U+FF09) (inputenc) not set up for use with LaTeX. See the inputenc package documentation for explanation. Type H <return> for immediate help. ... l.14 ... s（1+e^-（x-\mu）/s）^2，\end{split} ! Package inputenc Error: Unicode character ， (U+FF0C) (inputenc) not set up for use with LaTeX. See the inputenc package documentation for explanation. Type H <return> for immediate help. ... l.14 ... s（1+e^-（x-\mu）/s）^2，\end{split} ! Missing } inserted. <inserted text> } l.14 ... s（1+e^-（x-\mu）/s）^2，\end{split} [1] (./math.aux) ) (see the transcript file for additional information) Output written on math.dvi (1 page, 520 bytes). Transcript written on math.log.
在哪里？ =位置和 =比例尺。
在极端值问题中，逻辑分布可以作为Gumbel分布的混合，在流行病学中，以及由国际象棋联合会（FID）使用，在ELO排名系统中，假设每个玩家的表现是一个逻辑分布的随机变量。
工具书类
Reiss，R.-D.和Thomas M.（2001），“保险、金融、水文和其他领域的极值统计分析”，Birkhauser Verlag，巴塞尔，第132-133页。
物流配送〉，选自MathWorld——Wolfram网络资源。http://mathworld.wolfram.com/logisticdistribution.html
维基百科，“物流配送”，https://en.wikipedia.org/wiki/logistic_distribution
实例
从分发中抽取样本：
>>> loc, scale = 10, 1 >>> s = np.random.default_rng().logistic(loc, scale, 10000) >>> import matplotlib.pyplot as plt >>> count, bins, ignored = plt.hist(s, bins=50)
#按分布绘制
>>> def logist(x, loc, scale): ... return np.exp((loc-x)/scale)/(scale*(1+np.exp((loc-x)/scale))**2) >>> lgst_val = logist(bins, loc, scale) >>> plt.plot(bins, lgst_val * count.max() / lgst_val.max()) >>> plt.show()