code: def add_time_dependent_effects(self, ts):
          
          destts = Vectors.dense([0] * len(ts))
          result =  self._jmodel.addTimeDependentEffects(_py2java(self._ctx, Vectors.dense(ts)), _py2java(self._ctx, destts))
          return _java2py(self._ctx, result.toArray())
docs: Given a timeseries, apply a model to it.
          
          Parameters
          ----------
          ts:
              Time series of i.i.d. observations as a Numpy array
          
          returns the time series with added time-dependent effects as a Numpy array.