
{{alias}}( [α, β] )
    Returns a beta distribution object.

    Parameters
    ----------
    α: number (optional)
        First shape parameter. Must be greater than `0`. Default: `1.0`.

    β: number (optional)
        Second shape parameter. Must be greater than `0`. Default: `1.0`.

    Returns
    -------
    beta: Object
        Distribution instance.

    beta.alpha: number
        First shape parameter. If set, the value must be greater than `0`.

    beta.beta: number
        Second shape parameter. If set, the value must be greater than `0`.

    beta.entropy: number
        Read-only property which returns the differential entropy.

    beta.kurtosis: number
        Read-only property which returns the excess kurtosis.

    beta.mean: number
        Read-only property which returns the expected value.

    beta.median: number
        Read-only property which returns the median.

    beta.mode: number
        Read-only property which returns the mode.

    beta.skewness: number
        Read-only property which returns the skewness.

    beta.stdev: number
        Read-only property which returns the standard deviation.

    beta.variance: number
        Read-only property which returns the variance.

    beta.cdf: Function
        Evaluates the cumulative distribution function (CDF).

    beta.logcdf: Function
        Evaluates the natural logarithm of the cumulative distribution function
        (CDF).

    beta.logpdf: Function
        Evaluates the natural logarithm of the probability density function
        (PDF).

    beta.mgf: Function
        Evaluates the moment-generating function (MGF).

    beta.pdf: Function
        Evaluates the probability density function (PDF).

    beta.quantile: Function
        Evaluates the quantile function at probability `p`.

    Examples
    --------
    > var beta = {{alias}}( 1.0, 1.0 );
    > beta.alpha
    1.0
    > beta.beta
    1.0
    > beta.entropy
    0.0
    > beta.kurtosis
    -1.2
    > beta.mean
    0.5
    > beta.median
    0.5
    > beta.mode
    NaN
    > beta.skewness
    0.0
    > beta.stdev
    ~0.289
    > beta.variance
    ~0.0833
    > beta.cdf( 0.8 )
    0.8
    > beta.logcdf( 0.8 )
    ~-0.223
    > beta.logpdf( 1.0 )
    0.0
    > beta.mgf( 3.14 )
    ~7.0394
    > beta.pdf( 1.0 )
    1.0
    > beta.quantile( 0.8 )
    0.8

    See Also
    --------

