
{{alias}}( [r, p] )
    Returns a negative binomial distribution object.

    Parameters
    ----------
    r: number (optional)
        Number of successes until experiment is stopped. Must be a positive
        number. Default: `1`.

    p: number (optional)
        Success probability. Must be a number between `0` and `1`. Default:
        `0.5`.

    Returns
    -------
    nbinomial: Object
        Distribution instance.

    nbinomial.r: number
        Number of trials. If set, the value must be a positive number.

    nbinomial.p: number
        Success probability. If set, the value must be a number between `0` and
        `1`.

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

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

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

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

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

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

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

    nbinomial.logpmf: Function
        Evaluates the natural logarithm of the probability mass function (PMF).

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

    nbinomial.pmf: Function
        Evaluates the probability mass function (PMF).

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

    Examples
    --------
    > var nbinomial = {{alias}}( 8.0, 0.5 );
    > nbinomial.r
    8.0
    > nbinomial.p
    0.5
    > nbinomial.kurtosis
    0.8125
    > nbinomial.mean
    8.0
    > nbinomial.mode
    7.0
    > nbinomial.skewness
    0.75
    > nbinomial.stdev
    4.0
    > nbinomial.variance
    16.0
    > nbinomial.cdf( 2.9 )
    ~0.055
    > nbinomial.logpmf( 3.0 )
    ~-2.837
    > nbinomial.mgf( 0.2 )
    ~36.675
    > nbinomial.pmf( 3.0 )
    ~0.059
    > nbinomial.quantile( 0.8 )
    11.0

    See Also
    --------

