1 Residual norm, norm of normal equations, and matrix norm for regressor_linear_ solve. 2 0 KSP resid norm 1.516575088810e+00 3 1 KSP resid norm 7.758996082099e-01 normal eq resid norm 8.408142938043e-01 matrix norm 1.228473174906e+00 4 2 KSP resid norm 3.380617018914e-01 normal eq resid norm 2.920128359737e-16 matrix norm 1.837117307087e+00 5PetscRegressor Object: 1 MPI process 6 type: linear 7 PetscRegressor Linear Type: ols 8 KSP Object: (regressor_linear_) 1 MPI process 9 type: lsqr 10 standard error not computed 11 using inexact matrix norm 12 maximum iterations=10000, initial guess is zero 13 tolerances: relative=1e-05, absolute=1e-50, divergence=10000. 14 left preconditioning 15 using UNPRECONDITIONED norm type for convergence test 16 PC Object: (regressor_linear_) 1 MPI process 17 type: none 18 linear system matrix, followed by the matrix used to construct the preconditioner: 19 Mat Object: 1 MPI process 20 type: composite 21 rows=5, cols=2 22 Mat Object: 1 MPI process 23 type: normal 24 rows=2, cols=2 25 total KSP iterations: 2 26 Intercept=0.0857143 27Intercept is 0.085714 28Coefficients are 29Vec Object: 1 MPI process 30 type: seq 310.4 321.42857 33Predicted values are 34Vec Object: 1 MPI process 35 type: seq 361.11429 370.242857 380.0857143 390.642857 401.91429 41