mx.nd.random.pdf.normal¶

Description¶

Computes the value of the PDF of sample of normal distributions with parameters mu (mean) and sigma (standard deviation).

mu and sigma must have the same shape, which must match the leftmost subshape of sample. That is, sample can have the same shape as mu and sigma, in which case the output contains one density per distribution, or sample can be a tensor of tensors with that shape, in which case the output is a tensor of densities such that the densities at index i in the output are given by the samples at index i in sample parameterized by the values of mu and sigma at index i.

Example:

sample = [[-2, -1, 0, 1, 2]]
random_pdf_normal(sample=sample, mu=[0], sigma=[1]) =
[[0.05399097, 0.24197073, 0.3989423, 0.24197073, 0.05399097]]

random_pdf_normal(sample=sample*2, mu=[0,0], sigma=[1,2]) =
[[0.05399097, 0.24197073, 0.3989423,  0.24197073, 0.05399097],
[0.12098537, 0.17603266, 0.19947115, 0.17603266, 0.12098537]]


Arguments¶

Argument

Description

sample

NDArray-or-Symbol.

Samples from the distributions.

mu

NDArray-or-Symbol.

Means of the distributions.

is.log

boolean, optional, default=0.

If set, compute the density of the log-probability instead of the probability.

sigma

NDArray-or-Symbol.

Standard deviations of the distributions.

Value¶

out The result mx.ndarray