python - python 中 qq-plot(或 probplot)的逐点置信度包络线

Question

我有一个到达间隔时间列表，我正在使用 scipy.stats.probplot 绘制概率图(类似于 qq-plot)。我的数据在列表 l 中，我调用

scipy.stats.probplot(l, dist=stats.expon)

如何向图中添加逐点置信度包络线。以前的 SO answer展示了如何在 R 中执行此操作，但我需要在 python 中执行此操作。

我也尝试了 statsmodels，但它的功能似乎比等效的 scipy 略少(例如，它不计算 R^2 错误)。

Answer 1

我发布了一个稍微不同的例子，但它可能帮你...

#!/usr/bin/env python

from scipy.stats import t
from numpy import average, std
from math import sqrt

if __name__ == '__main__':
    # data we want to evaluate: average height of 30 one year old male and
    # female toddlers. Interestingly, at this age height is not bimodal yet
    data = [63.5, 81.3, 88.9, 63.5, 76.2, 67.3, 66.0, 64.8, 74.9, 81.3, 76.2,
            72.4, 76.2, 81.3, 71.1, 80.0, 73.7, 74.9, 76.2, 86.4, 73.7, 81.3,
            68.6, 71.1, 83.8, 71.1, 68.6, 81.3, 73.7, 74.9]
    mean = average(data)
    # evaluate sample variance by setting delta degrees of freedom (ddof) to
    # 1. The degree used in calculations is N - ddof
    stddev = std(data, ddof=1)
    # Get the endpoints of the range that contains 95% of the distribution
    t_bounds = t.interval(0.95, len(data) - 1)
    # sum mean to the confidence interval
    ci = [mean + critval * stddev / sqrt(len(data)) for critval in t_bounds]
    print "Mean: %f" % mean
    print "Confidence Interval 95%%: %f, %f" % (ci[0], ci[1])