class_docstr: Results class for Gaussian process regression models.
code: def predict(self, exog=None, transform=True, *args, **kwargs):
      if not transform:
          warnings.warn("'transform=False' is ignored in predict")
  
      if len(args) > 0 or len(kwargs) > 0:
          warnings.warn("extra arguments ignored in 'predict'")
  
      return self.model.predict(self.params, exog)
  
imports: import numpy
  import pandas
  import patsy
  import statsmodels.base.model
  from statsmodels.regression.linear_model import OLS
  import collections
  from scipy.optimize import minimize
  from statsmodels.iolib import summary2
  from statsmodels.tools.numdiff import approx_fprime
  import warnings
label_desc: Use image node_id 2 for calling the ProcessMLEResults obj's underlying member method code with example usage: obj.predict(exog, transform) and returns: self