class_docstr: Quadratic model
  
  This model is defined by :math:`y = \beta_0 x^2 + \beta_1 x + \beta_2`
  
  Examples
  --------
  We can calculate orthogonal distance regression with a quadratic model:
  
  >>> from scipy import odr
  >>> import numpy as np
  >>> x = np.linspace(0.0, 5.0)
  >>> y = 1.0 * x ** 2 + 2.0 * x + 3.0
  >>> data = odr.Data(x, y)
  >>> odr_obj = odr.ODR(data, odr.quadratic)
  >>> output = odr_obj.run()
  >>> print(output.beta)
  [1. 2. 3.]
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code: def __init__(self):
      super().__init__(
          _quadratic,
          fjacd=_quad_fjd,
          fjacb=_quad_fjb,
          estimate=_quad_est,
          meta={
              "name": "Quadratic",
              "equ": "y = B_0*x**2 + B_1*x + B_2",
              "TeXequ": "$y = \\beta_0 x^2 + \\beta_1 x + \\beta_2",
          },
      )
  
imports: import numpy
  from scipy.odr._odrpack import Model
label_desc: Use image node_id 1 to create a new _QuadraticModel object from inherited base classes: Model with example: obj = _QuadraticModel()