class_docstr: Generalized least squares model with a general covariance structure
      
class_docstr_tok: ["Generalized","least","squares","model","with","a","general","covariance","structure"]
code: def __init__(self, design, sigma):
      self.cholsigmainv = npl.cholesky(npl.pinv(sigma)).T
      super().__init__(design)
  
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 GLSModel object from inherited base classes: OLSModel with example: obj = GLSModel(design, sigma)