def convert_exponent_alpha(exponent):
    """Convert a powerlaw exponent to the expected DFA alpha value.

    Parameters
    ----------
    exponent : float
        Aperiodic exponent value, representing a 1/f distribution.

    Returns
    -------
    alpha : float
        Predicted DFA alpha value for the given exponent value.

    References
    ----------
    .. [1] Schaefer, A., Brach, J. S., Perera, S., & Sejdić, E. (2014). A comparative analysis
           of spectral exponent estimation techniques for 1/fβ processes with applications to the
           analysis of stride interval time series. Journal of Neuroscience Methods, 222, 118–130.
           https://doi.org/10.1016/j.jneumeth.2013.10.017

    Examples
    --------
    Convert a powerlaw exponent for pink noise to the expected DFA value:

    >>> convert_exponent_alpha(-1)
    1.0

    Convert a powerlaw exponent for white noise to the expected DFA value:

    >>> convert_exponent_alpha(0)
    0.5
    """

    return (-exponent + 1) / 2.