ndex the elements of
    `x` and the last index is the degree of the HermiteE polynomial.

    If `c` is a 1-D array of coefficients of length `n + 1` and `V` is the
    array ``V = hermevander(x, n)``, then ``np.dot(V, c)`` and
    ``hermeval(x, c)`` are the same up to roundoff. This equivalence is
    useful both for least squares fitting and for the evaluation of a large
    number of HermiteE series of the same degree and sample points.

    Parameters
    ----------
    x : array_like
        Array of points. The dtype is converted to float64 or complex128
        depending on whether any of the elements are complex. If `x` is
        scalar it is converted to a 1-D array.
    deg : int
        Degree of the resulting matrix.

    Returns
    -------
    vander : ndarray
        The pseudo-Vandermonde matrix. The shape of the returned matrix is
        ``x.shape + (deg + 1,)``, where The last index is the degree of the
        corresponding HermiteE polynomial.  The dtype will be the same as
        the converted `x`.

    Examples
    --------
    >>> from numpy.polynomial.hermite_e import hermevander
    >>> x = np.array([-1, 0, 1])
    >>> hermevander(x, 3)
    array([[ 1., -1.,  0.,  2.],
           [ 1.,  0., -1., -0.],
           [ 1.,  1.,  0., -2.]])

    r*