Last active
August 29, 2015 14:05
-
-
Save 3kwa/df3a6f512fba18a85c8c to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
""" | |
Bootstrap in Python using numpy ... mind expanding! | |
source: http://people.duke.edu/~ccc14/pcfb/analysis.html | |
""" | |
from collections import namedtuple | |
import numpy | |
CI = namedtuple('CI', ['lower', 'upper']) | |
def bootstrap(data, num_samples, statistic, percentage): | |
""" | |
returns the bootstrap estimate of ci for statistic | |
data is a numpy.array | |
num_samples (an integer) is the number of samples with replacement to use | |
statistic is the statistical (universal) function to compute | |
percentage is the confidence interval range | |
>>> bootstrap(numpy.array([1, 4, 2, 5, 6, 2, 3, 5]), | |
... 1000, | |
... numpy.mean, | |
... 95) # doctest: +ELLIPSIS | |
CI(lower=..., upper=...) | |
""" | |
N = len(data) | |
index = numpy.random.randint(0, N, (num_samples, N)) | |
samples = data[index] | |
alpha = 1 - percentage / 100. | |
statistics = numpy.sort(statistic(samples, 1)) | |
return CI(statistics[int((alpha / 2) * num_samples)], | |
statistics[int((1 - alpha / 2) * num_samples)]) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment