在python中执行引导时初始化np.empty（）问题意外输出

Question

我是python的初学者，正在学习统计学！ 遇到一些函数的问题，这些函数帮助引导数据数组n次，并在数组中输出每个引导的平均值

提前谢谢你的帮助

import numpy as np

np.random.seed(42)

rainfall = np.array([875.5, 648.2, 788.1, 940.3, 491.1, 743.5, 730.1, 686.5,
                     878.8, 865.6, 654.9, 831.5, 798.1, 681.8, 743.8, 689.1,
                     752.1, 837.2, 710.6, 749.2, 967.1, 701.2, 619., 747.6,
                     803.4, 645.6, 804.1, 787.4, 646.8, 997.1, 774., 734.5,
                     835., 840.7, 659.6, 828.3, 909.7, 856.9, 578.3, 904.2,
                     883.9, 740.1, 773.9, 741.4, 866.8, 871.1, 712.5, 919.2,
                     927.9, 809.4, 633.8, 626.8, 871.3, 774.3, 898.8, 789.6,
                     936.3, 765.4, 882.1, 681.1, 661.3, 847.9, 683.9, 985.7,
                     771.1, 736.6, 713.2, 774.5, 937.7, 694.5, 598.2, 983.8,
                     700.2, 901.3, 733.5, 964.4, 609.3, 1035.2, 718., 688.6,
                     736.8, 643.3, 1038.5, 969., 802.7, 876.6, 944.7, 786.6,
                     770.4, 808.6, 761.3, 774.2, 559.3, 674.2, 883.6, 823.9,
                     960.4, 877.8, 940.6, 831.8, 906.2, 866.5, 674.1, 998.1,
                     789.3, 915., 737.1, 763., 666.7, 824.5, 913.8, 905.1,
                     667.8, 747.4, 784.7, 925.4, 880.2, 1086.9, 764.4, 1050.1,
                     595.2, 855.2, 726.9, 785.2, 948.8, 970.6, 896., 618.4,
                     572.4, 1146.4, 728.2, 864.2, 793.])



def bootstrap_replicate_1d(data, func):
   """Generate bootstrap replicate of 1D data."""
   bs_sample = np.random.choice(data, len(data))

   return func(bs_sample)

print(bootstrap_replicate_1d(rainfall, np.mean))

Output: 816.7992481203007

Data output make sense as the mean rainfall data is around 800.

def draw_bs_reps(data, func, size=1):
   """Draw bootstrap replicates."""

   # Initialize array of replicates: bs_replicates
   bs_replicates = np.empty(size)  

   # Generate replicates
   for i in range(size):
   bootstrap_replicate_1d(data, func)

   return bs_replicates

test = draw_bs_reps(rainfall, np.mean, 1)

Output: array([105804.1])

test = draw_bs_reps(rainfall, np.mean, 5)

Output: array([3.3 , 4. , 4.35 , 4.6 , 4.9775])

The result of the function seems to be erroneous as the mean deviates a lot, even worse when the size is increased.

Answer 1

未启动bs_复制，但未将其重新分配到要编辑的for循环、draw_bs_reps函数中：

def draw_bs_reps(data, func, size=1):
   """Draw bootstrap replicates."""

   # Initialize array of replicates: bs_replicates
   bs_replicates = np.empty(size)  

   # Generate replicates
   for i in range(size):
   bs_replicates[i] = bootstrap_replicate_1d(data, func)

   return bs_replicates