`scipy.stats._morestats:mvsdist`

source: /scipy/stats/_morestats.py :162

Signature

def mvsdist ( data )

Summary

'Frozen' distributions for mean, variance, and standard deviation of data.

Parameters

data : array_like: Input array. Converted to 1-D using ravel. Requires 2 or more data-points.

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.

Notes

The return values from bayes_mvs(data) is equivalent to tuple((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 from bayes_mvs.

Array API Standard Support

mvsdist has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ⛔                   
PyTorch               ⛔                     ⛔                   
JAX                   ⛔                     ⛔                   
Dask                  ⛔                     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

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()
mean.interval(0.95)
mean.std()

✗

Aliases

scipy.stats.mvsdist