The R package “SparseM” provides useful functions for various matrix operations including coercion and linear equation solving. Linear regression with sparse data is implemented by generalizing the “lm” function to achieve similar functionality with “slm, print.summary.slm” functions. Of course, ...
str(sdf)deftest_array_interface(self):res = np.sqrt(self.frame) dres = np.sqrt(self.frame.to_dense()) tm.assert_frame_equal(res.to_dense(), dres)deftest_pickle(self):def_test_roundtrip(frame, orig):result = tm.round_trip_pickle(frame) tm.assert_sp_frame_equal(frame, result) tm...
S e 2007, the Matrix package has been providing coercion from a factor object to a sparseMatrix o produce the transpose of the model matrix corresponding to a model with that factor as predictor (and no intercept): as(f1, sparseMatrix) 6 x 20 sparse Matrix of class dgCMatrix _ . . ....