(name, rate)
return rv(name, ExponentialDistribution, (rate, ))
r"""
    Create a continuous random variable with an Exponential distribution.

    The density of the exponential distribution is given by

    .. math::
        f(x) := \lambda \exp(-\lambda x)

    with `x > 0`. Note that the expected value is `1/\lambda`.

    Parameters
    ==========

    rate : A positive Real number, `\lambda > 0`, the rate (or inverse scale/inverse mean)

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Exponential, density, cdf, E
    >>> from sympy.stats import variance, std, skewness
    >>> from sympy import Symbol

    >>> l = Symbol("lambda", positive=True)
    >>> z = Symbol("z")

    >>> X = Exponential("x", l)

    >>> density(X)(z)
    lambda*exp(-lambda*z)

    >>> cdf(X)(z)
    Piecewise((1 - exp(-lambda*z), z >= 0), (0, True))

    >>> E(X)
    1/lambda

    >>> variance(X)
    lambda**(-2)

    >>> skewness(X)
    2

    >>> X = Exponential('x', 10)

    >>> density(X)(z)
    10*exp(-10*z)

    >>> E(X)
    1/10

    >>> std(X)
    1/10

    References
    ==========

    .. [1] http://en.wikipedia.org/wiki/Exponential_distribution
    .. [2] http://mathworld.wolfram.com/ExponentialDistribution.html
r"""
    Create a continuous random variable with an Exponential distribution.
r Create a continuous random variable with an Exponential distribution .
def Exponential(name, rate):
    r"""
    Create a continuous random variable with an Exponential distribution.

    The density of the exponential distribution is given by

    .. math::
        f(x) := \lambda \exp(-\lambda x)

    with `x > 0`. Note that the expected value is `1/\lambda`.

    Parameters
    ==========

    rate : A positive Real number, `\lambda > 0`, the rate (or inverse scale/inverse mean)

    Returns
    =======

    A RandomSymbol.

    Examples
    ========

    >>> from sympy.stats import Exponential, density, cdf, E
    >>> from sympy.stats import variance, std, skewness
    >>> from sympy import Symbol

    >>> l = Symbol("lambda", positive=True)
    >>> z = Symbol("z")

    >>> X = Exponential("x", l)

    >>> density(X)(z)
    lambda*exp(-lambda*z)

    >>> cdf(X)(z)
    Piecewise((1 - exp(-lambda*z), z >= 0), (0, True))

    >>> E(X)
    1/lambda

    >>> variance(X)
    lambda**(-2)

    >>> skewness(X)
    2

    >>> X = Exponential('x', 10)

    >>> density(X)(z)
    10*exp(-10*z)

    >>> E(X)
    1/10

    >>> std(X)
    1/10

    References
    ==========

    .. [1] http://en.wikipedia.org/wiki/Exponential_distribution
    .. [2] http://mathworld.wolfram.com/ExponentialDistribution.html
    """

    return rv(name, ExponentialDistribution, (rate, ))
def Exponential ( name , rate ) : return rv ( name , ExponentialDistribution , ( rate , ) )