class_docstr: A simple default backend that stores the chain in memory
class_docstr_tok: ["A","simple","default","backend","that","stores","the","chain","in","memory"]
docstr: Compute an estimate of the autocorrelation time for each parameter
  
  Args:
      thin (Optional[int]): Use only every ``thin`` steps from the
          chain. The returned estimate is multiplied by ``thin`` so the
          estimated time is in units of steps, not thinned steps.
          (default: ``1``)
      discard (Optional[int]): Discard the first ``discard`` steps in
          the chain as burn-in. (default: ``0``)
  
  Other arguments are passed directly to
  :func:`emcee.autocorr.integrated_time`.
  
  Returns:
      array[ndim]: The integrated autocorrelation time estimate for the
          chain for each parameter.
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code: def get_autocorr_time(self, discard=0, thin=1, **kwargs):
      """Compute an estimate of the autocorrelation time for each parameter
  
      Args:
          thin (Optional[int]): Use only every ``thin`` steps from the
              chain. The returned estimate is multiplied by ``thin`` so the
              estimated time is in units of steps, not thinned steps.
              (default: ``1``)
          discard (Optional[int]): Discard the first ``discard`` steps in
              the chain as burn-in. (default: ``0``)
  
      Other arguments are passed directly to
      :func:`emcee.autocorr.integrated_time`.
  
      Returns:
          array[ndim]: The integrated autocorrelation time estimate for the
              chain for each parameter.
  
      """
      x = self.get_chain(discard=discard, thin=thin)
      return thin * autocorr.integrated_time(x, **kwargs)
  
imports: import numpy
  from ..None import autocorr
  from ..state import State
label_desc: Use image node_id 9 for calling the Backend obj's underlying member method code with example usage: obj.get_autocorr_time(discard, thin) and returns: unknown