class_docstr: class to reparameterize a model for standardized exog
  
  Parameters
  ----------
  data : array_like
      data that is standardized along axis=0
  ddof : None or int
      degrees of freedom for calculation of standard deviation.
      default is 1, in contrast to numpy.std
  const_idx : None or int
      If None, then the presence of a constant is detected if the standard
      deviation of a column is **equal** to zero. A constant column is
      not transformed. If this is an integer, then the corresponding column
      will not be transformed.
  demean : bool, default is True
      If demean is true, then the data will be demeaned, otherwise it will
      only be rescaled.
  
  Notes
  -----
  Warning: Not all options are tested and it is written for one use case.
  API changes are expected.
  
  This can be used to transform only the design matrix, exog, in a model,
  which is required in some discrete models when the endog cannot be rescaled
  or demeaned.
  The transformation is full rank and does not drop the constant.
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docstr: Transform parameters of the standardized model to the original model
  
  Parameters
  ----------
  params : ndarray
      parameters estimated with the standardized model
  
  Returns
  -------
  params_new : ndarray
      parameters transformed to the parameterization of the original
      model
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code: def transform_params(self, params):
      """Transform parameters of the standardized model to the original model
  
      Parameters
      ----------
      params : ndarray
          parameters estimated with the standardized model
  
      Returns
      -------
      params_new : ndarray
          parameters transformed to the parameterization of the original
          model
      """
  
      params_new = params / self.scale
      if self.const_idx != "n":
          params_new[self.const_idx] -= (params_new * self.mean).sum()
  
      return params_new
  
imports: import numpy
label_desc: Use image node_id 3 for calling the StandardizeTransform obj's underlying member method code with example usage: obj.transform_params(params) and returns: params_new