LostTech.TensorFlow : API Documentation

Type Normal

Namespace tensorflow.distributions

Parent Distribution

Interfaces INormal

The Normal distribution with location `loc` and `scale` parameters.

#### Mathematical details

The probability density function (pdf) is,

```none pdf(x; mu, sigma) = exp(-0.5 (x - mu)**2 / sigma**2) / Z Z = (2 pi sigma**2)**0.5 ```

where `loc = mu` is the mean, `scale = sigma` is the std. deviation, and, `Z` is the normalization constant.

The Normal distribution is a member of the [location-scale family]( https://en.wikipedia.org/wiki/Location-scale_family), i.e., it can be constructed as,

```none X ~ Normal(loc=0, scale=1) Y = loc + scale * X ```

#### Examples

Examples of initialization of one or a batch of distributions. Arguments are broadcast when possible.
Show Example
```import tensorflow_probability as tfp
tfd = tfp.distributions  # Define a single scalar Normal distribution.
dist = tfd.Normal(loc=0., scale=3.)  # Evaluate the cdf at 1, returning a scalar.
dist.cdf(1.)  # Define a batch of two scalar valued Normals.
# The first has mean 1 and standard deviation 11, the second 2 and 22.
dist = tfd.Normal(loc=[1, 2.], scale=[11, 22.])  # Evaluate the pdf of the first distribution on 0, and the second on 1.5,
# returning a length two tensor.
dist.prob([0, 1.5])  # Get 3 samples, returning a 3 x 2 tensor.
dist.sample([3]) ```

Public properties

objectloc get;

Distribution parameter for the mean.

objectloc_dyn get;

Distribution parameter for the mean.

objectscale get;

Distribution parameter for standard deviation.

objectscale_dyn get;

Distribution parameter for standard deviation.