code: def pltacorr(self, x, **kwargs):
      r"""
      call signature::
  
          acorr(x, normed=True, detrend=detrend_none, usevlines=True,
                maxlags=10, **kwargs)
  
      Plot the autocorrelation of *x*.  If *normed* = *True*,
      normalize the data by the autocorrelation at 0-th lag.  *x* is
      detrended by the *detrend* callable (default no normalization).
  
      Data are plotted as ``plot(lags, c, **kwargs)``
  
      Return value is a tuple (*lags*, *c*, *line*) where:
  
        - *lags* are a length 2*maxlags+1 lag vector
  
        - *c* is the 2*maxlags+1 auto correlation vector
  
        - *line* is a :class:`~matplotlib.lines.Line2D` instance
          returned by :meth:`plot`
  
      The default *linestyle* is None and the default *marker* is
      ``'o'``, though these can be overridden with keyword args.
      The cross correlation is performed with
      :func:`numpy.correlate` with *mode* = 2.
  
      If *usevlines* is *True*, :meth:`~matplotlib.axes.Axes.vlines`
      rather than :meth:`~matplotlib.axes.Axes.plot` is used to draw
      vertical lines from the origin to the acorr.  Otherwise, the
      plot style is determined by the kwargs, which are
      :class:`~matplotlib.lines.Line2D` properties.
  
      *maxlags* is a positive integer detailing the number of lags
      to show.  The default value of *None* will return all
      :math:`2 \mathrm{len}(x) - 1` lags.
  
      The return value is a tuple (*lags*, *c*, *linecol*, *b*)
      where
  
      - *linecol* is the
        :class:`~matplotlib.collections.LineCollection`
  
      - *b* is the *x*-axis.
  
      .. seealso::
  
          :meth:`~matplotlib.axes.Axes.plot` or
          :meth:`~matplotlib.axes.Axes.vlines`
             For documentation on valid kwargs.
  
      **Example:**
  
      :func:`~matplotlib.pyplot.xcorr` above, and
      :func:`~matplotlib.pyplot.acorr` below.
  
      **Example:**
  
      .. plot:: mpl_examples/pylab_examples/xcorr_demo.py
      """
      return self.xcorr(x, x, **kwargs)
  
imports: import numpy
  from numpy.testing import assert_array_almost_equal
  import matplotlib.pyplot
  from statsmodels import regression
  from statsmodels.tsa.arima_process import arma_generate_sample, arma_impulse_response
  from statsmodels.tsa.arima_process import arma_acovf, arma_acf
  from statsmodels.tsa.arima.model import ARIMA
  from statsmodels.tsa.stattools import acf, acovf
  from statsmodels.graphics.tsaplots import plot_acf
label_desc: Use image node_id 13 for calling a global function with example usage: pltacorr(x) and returns: self