# scipy.odr.quadratic

scipy.odr.quadratic = <scipy.odr.models._QuadraticModel object>

  Quadratic model

  This model is defined by \(y = \beta_0 x^2 + \beta_1 x + \beta_2\)

  Examples

  We can calculate orthogonal distance regression with a quadratic model:

      >>> from scipy import odr
      >>> 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.]

scipy.odr.unilinear Optimization and root finding (`scipy.optimize`)