class_docstr: Arbitrary-dimensional linear model
  
  This model is defined by :math:`y=\beta_0 + \sum_{i=1}^m \beta_i x_i`
  
  Examples
  --------
  We can calculate orthogonal distance regression with an arbitrary
  dimensional linear model:
  
  >>> from scipy import odr
  >>> import numpy as np
  >>> x = np.linspace(0.0, 5.0)
  >>> y = 10.0 + 5.0 * x
  >>> data = odr.Data(x, y)
  >>> odr_obj = odr.ODR(data, odr.multilinear)
  >>> output = odr_obj.run()
  >>> print(output.beta)
  [10.  5.]
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code: def __init__(self):
      super().__init__(
          _lin_fcn,
          fjacb=_lin_fjb,
          fjacd=_lin_fjd,
          estimate=_lin_est,
          meta={
              "name": "Arbitrary-dimensional Linear",
              "equ": "y = B_0 + Sum[i=1..m, B_i * x_i]",
              "TeXequ": r"$y=\beta_0 + \sum_{i=1}^m \beta_i x_i$",
          },
      )
  
imports: import numpy
  from scipy.odr._odrpack import Model
label_desc: Use image node_id 1 to create a new _MultilinearModel object from inherited base classes: Model with example: obj = _MultilinearModel()