code: def fit_model(ts, regressors, method="cochrane-orcutt", optimizationArgs=None, sc=None):
      
      assert sc != None, "Missing SparkContext"
      
      jvm = sc._jvm
      
      jmodel = jvm.com.cloudera.sparkts.models.RegressionARIMA.fitModel(_nparray2breezevector(sc, ts), _nparray2breezematrix(sc, regressors), method, _py2scala_seq(sc, optimizationArgs))
      return RegressionARIMAModel(jmodel=jmodel, sc=sc)
docs: Parameters
      ----------
      ts:
          time series to which to fit an ARIMA model as a Numpy array
      regressors:
          regression matrix as a Numpy array
      method:
          Regression method. Currently, only "cochrane-orcutt" is supported.
      optimizationArgs:
          
      sc:
          The SparkContext, required.
      
      returns an RegressionARIMAModel