scipy.stats.mvsdist¶

scipy.stats.
mvsdist
(data)[source]¶ ‘Frozen’ distributions for mean, variance, and standard deviation of data.
 Parameters
 dataarray_like
Input array. Converted to 1D using ravel. Requires 2 or more datapoints.
 Returns
 mdist“frozen” distribution object
Distribution object representing the mean of the data
 vdist“frozen” distribution object
Distribution object representing the variance of the data
 sdist“frozen” distribution object
Distribution object representing the standard deviation of the data
See also
Notes
The return values from
bayes_mvs(data)
is equivalent totuple((x.mean(), x.interval(0.90)) for x in mvsdist(data))
.In other words, calling
<dist>.mean()
and<dist>.interval(0.90)
on the three distribution objects returned from this function will give the same results that are returned frombayes_mvs
.References
T.E. Oliphant, “A Bayesian perspective on estimating mean, variance, and standarddeviation from data”, https://scholarsarchive.byu.edu/facpub/278, 2006.
Examples
>>> from scipy import stats >>> data = [6, 9, 12, 7, 8, 8, 13] >>> mean, var, std = stats.mvsdist(data)
We now have frozen distribution objects “mean”, “var” and “std” that we can examine:
>>> mean.mean() 9.0 >>> mean.interval(0.95) (6.6120585482655692, 11.387941451734431) >>> mean.std() 1.1952286093343936