'Calculate moments (mean, variance) of distribution in python
I have two arrays. x is the independent variable, and counts is the number of counts of x occurring, like a histogram. I know I can calculate the mean by defining a function:
def mean(x,counts):
return np.sum(x*counts) / np.sum(counts)
Is there a general function I can use to calculate each moment from the distribution defined by x and counts? I would also like to compute the variance.
Solution 1:[1]
import scipy as sp
from scipy import stats
stats.moment(counts, moment = 2) #variance
stats.moment returns nth central moment.
Solution 2:[2]
Numpy supports order statistics now
https://numpy.org/doc/stable/reference/routines.statistics.html
np.averagenp.stdnp.varetc
Sources
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Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | |
| Solution 2 | Souradeep Nanda |