class_docstr: Student t copula.
  
  Parameters
  ----------
  corr : scalar or array_like
      Correlation or scatter matrix for the elliptical copula. In the
      bivariate case, ``corr` can be a scalar and is then considered as
      the correlation coefficient. If ``corr`` is None, then the scatter
      matrix is the identity matrix.
  df : float (optional)
      Degrees of freedom of the multivariate t distribution.
  k_dim : int
      Dimension, number of components in the multivariate random variable.
  
  Notes
  -----
  Elliptical copulas require that copula parameters are set when the
  instance is created. Those parameters currently cannot be provided in the
  call to methods. (This will most likely change in future versions.)
  If non-empty ``args`` are provided in methods, then a ValueError is raised.
  The ``args`` keyword is provided for a consistent interface across
  copulas.
  
  References
  ----------
  .. [1] Joe, Harry, 2014, Dependence modeling with copulas. CRC press.
      p. 181
code: def _arg_from_tau(self, tau):
      # for generic compat
      # this does not provide an estimate of df
      return self.corr_from_tau(tau)
  
imports: import numpy
  from scipy import stats
  from statsmodels.compat.scipy import multivariate_t
  from statsmodels.distributions.copula.copulas import Copula
label_desc: Use image node_id 5 for calling the StudentTCopula obj's underlying member method code with example usage: obj._arg_from_tau(tau) and returns: self