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:param actuals: A pandas series of the actual timeseries to forecast.
            It is assumed there are no missing data points,
            i.e. x[1] is the observation directly following x[0], etc.

:param trend_events: A list of dictionaries. Each dict should have the following entries
            - 'index' the start index of the event (i.e. index = i assumes the start of the event
                is at location actuals[i]). The index should be of the same type as the actuals index.
            - 'm0' the estimated gradient increase following the event
            - 'gamma' (Optional) the damping to use for the trend. This is a float between 0 and 1.
                It's not recommended to be below 0.8 and must be 0 > gamma <= 1.
                If gamma is missing from the dict, or gamma = 1, a linear trend is used (i.e. no damping).