class_docstr: Univariate linear model
  
  This model is defined by :math:`y = \beta_0 x + \beta_1`
  
  Examples
  --------
  We can calculate orthogonal distance regression with an unilinear model:
  
  >>> from scipy import odr
  >>> import numpy as np
  >>> x = np.linspace(0.0, 5.0)
  >>> y = 1.0 * x + 2.0
  >>> data = odr.Data(x, y)
  >>> odr_obj = odr.ODR(data, odr.unilinear)
  >>> output = odr_obj.run()
  >>> print(output.beta)
  [1. 2.]
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code: def __init__(self):
      super().__init__(
          _unilin,
          fjacd=_unilin_fjd,
          fjacb=_unilin_fjb,
          estimate=_unilin_est,
          meta={
              "name": "Univariate Linear",
              "equ": "y = B_0 * x + B_1",
              "TeXequ": "$y = \\beta_0 x + \\beta_1$",
          },
      )
  
imports: import numpy
  from scipy.odr._odrpack import Model
label_desc: Use image node_id 1 to create a new _UnilinearModel object from inherited base classes: Model with example: obj = _UnilinearModel()