class_docstr: A class to estimate AR(p) coefficients from residuals
class_docstr_tok: ["A","class","to","estimate","AR","(","p",")","coefficients","from","residuals"]
docstr: Bias-correcting AR estimation class
  
  Parameters
  ----------
  model : ``OSLModel`` instance
      A models.regression.OLSmodel instance,
      where `model` has attribute ``design``
  p : int, optional
      Order of AR(p) noise
code: def __init__(self, model, p=1):
      """Bias-correcting AR estimation class
  
      Parameters
      ----------
      model : ``OSLModel`` instance
          A models.regression.OLSmodel instance,
          where `model` has attribute ``design``
      p : int, optional
          Order of AR(p) noise
      """
      self.p = p
      self.invM = ar_bias_corrector(model.design, model.calc_beta, p)
  
imports: import warnings
  import numpy
  import numpy.linalg
  import scipy.linalg
  from nibabel.onetime import auto_attr
  from scipy import stats
  from nipy.algorithms.utils.matrices import matrix_rank, pos_recipr
  from .model import LikelihoodModel, LikelihoodModelResults
label_desc: Use image node_id 1 to create a new AREstimator object  with example: obj = AREstimator(model, p)