def METHOD_NAME(self, series: Union[TimeSeries, Sequence[TimeSeries]]) -> None:
    """Trains the detector on the given time series.
    Parameters
    ----------
    series
        Time series to be used to train the detector.
    Returns
    -------
    self
        Fitted Detector.
    """
    list_series = [series] if not isinstance(series, Sequence) else series
    raise_if_not(
        all([isinstance(s, TimeSeries) for s in list_series]),
        "all series in `series` must be of type TimeSeries.",
    )
    raise_if_not(
        all([s.is_deterministic for s in list_series]),
        "all series in `series` must be deterministic (number of samples equal to 1).",
    )
    self.width_trained_on = list_series[0].width
    raise_if_not(
        all([s.width == self.width_trained_on for s in list_series]),
        "all series in `series` must have the same number of components.",
    )
    self._fit_called = True
    return self._fit_core(list_series)