# LostTech.TensorFlow : API Documentation

Type Kumaraswamy

Namespace tensorflow.contrib.distributions

Parent TransformedDistribution

Interfaces IKumaraswamy

Kumaraswamy distribution.

The Kumaraswamy distribution is defined over the `(0, 1)` interval using parameters `concentration1` (aka "alpha") and `concentration0` (aka "beta"). It has a shape similar to the Beta distribution, but is reparameterizeable.

#### Mathematical Details

The probability density function (pdf) is,

```none pdf(x; alpha, beta) = alpha * beta * x**(alpha - 1) * (1 - x**alpha)**(beta - 1) ```

where:

* `concentration1 = alpha`, * `concentration0 = beta`,

Distribution parameters are automatically broadcast in all functions; see examples for details.

#### Examples

Show Example
```# Create a batch of three Kumaraswamy distributions.
alpha = [1, 2, 3]
beta = [1, 2, 3]
dist = Kumaraswamy(alpha, beta)  dist.sample([4, 5])  # Shape [4, 5, 3]  # `x` has three batch entries, each with two samples.
x = [[.1,.4,.5],
[.2,.3,.5]]
# Calculate the probability of each pair of samples under the corresponding
# distribution in `dist`.
dist.prob(x)         # Shape [2, 3] ```

### Public properties

#### Tensorconcentration0 get;

Concentration parameter associated with a `0` outcome.

#### objectconcentration0_dyn get;

Concentration parameter associated with a `0` outcome.

#### Tensorconcentration1 get;

Concentration parameter associated with a `1` outcome.

#### objectconcentration1_dyn get;

Concentration parameter associated with a `1` outcome.