'filter a time series using fftconvolve3 with ARMA filter
padding of x currently works only if x is 1d
in example it produces same observations at beginning as lfilter even
without padding.
TODO: this returns 1 additional observation at the end'

def filter2(self, x, pad=0):

    from statsmodels.tsa.filters import fftconvolve3
    if (not pad):
        pass
    elif (pad == 'auto'):
        x = self.padarr(x, (x.shape[0] + (2 * (self.nma + self.nar))), atend=False)
    else:
        x = self.padarr(x, (x.shape[0] + int(pad)), atend=False)
    return fftconvolve3(x, self.ma, self.ar)
