XrDiscreteRV

class xarray_einstats.stats.XrDiscreteRV(dist, *args, **kwargs)

Wrapper for subclasses of rv_discrete.

Usage examples available at Intro to the stats module

See also

xarray_einstats.stats.XrDiscreteRV

Examples

Evaluate the ppf of a Student-T distribution from DataArrays that need broadcasting:

from xarray_einstats import tutorial
from xarray_einstats.stats import XrDiscreteRV
from scipy import stats
ds = tutorial.generate_mcmc_like_dataset(3)
dist = XrDiscreteRV(stats.poisson, ds["mu"])
dist.ppf([.1, .5, .6])

<xarray.DataArray (quantile: 3, chain: 4, draw: 10, team: 6)> Size: 6kB
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 3.0 0.0 1.0 2.0 0.0 0.0 1.0 1.0 0.0
Coordinates:
  * quantile  (quantile) float64 24B 0.1 0.5 0.6
  * chain     (chain) int64 32B 0 1 2 3
  * draw      (draw) int64 80B 0 1 2 3 4 5 6 7 8 9
  * team      (team) <U1 24B 'a' 'b' 'c' 'd' 'e' 'f'

xarray.DataArray

• quantile: 3
• chain: 4
• draw: 10
• team: 6

• 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 1.0 2.0 0.0 0.0 1.0 1.0 0.0

  array([[[[0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 0., 1.],
           [0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 1., 0., 0.],
           [0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 2., 0.],
           [1., 0., 0., 0., 1., 0.],
           [0., 0., 1., 0., 2., 0.]],
  
          [[0., 0., 0., 1., 0., 0.],
           [1., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 0., 0.],
           [1., 0., 0., 0., 0., 0.],
           [0., 0., 1., 0., 0., 1.],
           [0., 0., 0., 0., 0., 0.],
           [0., 0., 0., 0., 0., 0.],
           [0., 1., 0., 1., 1., 0.],
           [0., 0., 0., 0., 0., 2.],
  ...
           [0., 2., 1., 0., 0., 1.],
           [2., 0., 0., 4., 1., 1.],
           [1., 0., 3., 0., 0., 0.],
           [2., 1., 2., 1., 0., 0.],
           [2., 0., 1., 1., 0., 1.],
           [0., 2., 3., 1., 0., 0.],
           [1., 1., 1., 1., 2., 0.],
           [1., 0., 1., 2., 1., 1.],
           [1., 0., 2., 2., 1., 1.]],
  
          [[0., 0., 2., 1., 1., 2.],
           [4., 3., 1., 0., 1., 0.],
           [4., 1., 2., 2., 0., 2.],
           [2., 2., 1., 2., 1., 1.],
           [0., 2., 2., 2., 0., 0.],
           [3., 1., 1., 1., 1., 0.],
           [2., 2., 5., 0., 1., 0.],
           [1., 1., 0., 2., 1., 1.],
           [0., 1., 4., 3., 0., 1.],
           [2., 0., 0., 1., 1., 0.]]]])

• Coordinates: (4)
  • quantile
    (quantile)
    float64
    0.1 0.5 0.6

    array([0.1, 0.5, 0.6])

  • chain
    (chain)
    int64
    0 1 2 3

    array([0, 1, 2, 3])

  • draw
    (draw)
    int64
    0 1 2 3 4 5 6 7 8 9

    array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

  • team
    (team)
    <U1
    'a' 'b' 'c' 'd' 'e' 'f'

    array(['a', 'b', 'c', 'd', 'e', 'f'], dtype='<U1')

Methods

XrDiscreteRV.__init__(dist, *args, **kwargs)
XrDiscreteRV.cdf(*args[, apply_kwargs])	Method wrapping .cdf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.isf(*args[, apply_kwargs])	Method wrapping .isf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.logcdf(*args[, apply_kwargs])	Method wrapping .logcdf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.logpmf(*args[, apply_kwargs])	Method wrapping .logpmf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.logsf(*args[, apply_kwargs])	Method wrapping .logsf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.pmf(*args[, apply_kwargs])	Method wrapping .pmf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.ppf(*args[, apply_kwargs])	Method wrapping .ppf of the input distribution with xarray.apply_ufunc
XrDiscreteRV.rvs(*args[, size, ...])	Method wrapping .rvs of the input distribution with xarray.apply_ufunc
XrDiscreteRV.sf(*args[, apply_kwargs])	Method wrapping .sf of the input distribution with xarray.apply_ufunc