estimator.nd.DiscreteGaussian#
- class estimator.nd.DiscreteGaussian(stddev, mean=0, n=None)[source]#
A discrete Gaussian distribution with standard deviation
stddev
per component.EXAMPLE:
>>> from estimator import * >>> ND.DiscreteGaussian(3.0, 1.0) D(σ=3.00, μ=1.00)
- __call__(**kwargs)#
Call self as a function.
Methods
__init__
(stddev[, mean, n])resize
(new_n)Return an altered distribution having a dimension new_n.
support_size
([fraction])Compute the size of the support covering the probability given as fraction.
Attributes
The number of non-zero coefficients in this distribution
Whether the value of coefficients are bounded
Whether the density of the distribution is < 1/2.