On Thu, Sep 9, 2010 at 7:22 PM, cpblpublic email@example.com wrote:
I am looking for some reaally basic statistical tools. I have some sample data, some sample weights for those measurements, and I want to calculate a mean and a standard error of the mean.
How about using a bootstrap?
Array and weights:
a = np.arange(100) w = np.random.rand(100) w = w / w.sum()
n = 1000 ma = np.zeros(n)
Save mean of each bootstrap sample:
for i in range(n):
....: idx = np.random.randint(0, 100, 100) ....: ma[i] = np.dot(a[idx], w[idx]) ....: ....:
Error in mean:
Hmm...should w[idx] be renormalized to sum to one in each bootstrap sample?