|
|
Previous | Next |
| ckbs_t_obj | Student's t Sum of Squares Objective |
| ckbs_t_grad | Student's t Gradient |
| ckbs_t_hess | Student's t Hessian |
| ckbs_diag_solve | Block Diagonal Algorithm |
| ckbs_bidiag_solve | Block Bidiagonal Algorithm |
| ckbs_bidiag_solve_t | Block Bidiagonal Algorithm |
| ckbs_blkbidiag_symm_mul | Packed Block Bidiagonal Matrix Symmetric Multiply |
| ckbs_blkdiag_mul | Packed Block Diagonal Matrix Times a Vector or Matrix |
| ckbs_blkdiag_mul_t | Transpose of Packed Block Diagonal Matrix Times a Vector or Matrix |
| ckbs_blkbidiag_mul_t | Packed Lower Block Bidiagonal Matrix Transpose Times a Vector |
| ckbs_blkbidiag_mul | Packed Lower Block Bidiagonal Matrix Times a Vector |
| ckbs_blktridiag_mul | Packed Block Tridiagonal Matrix Times a Vector |
| ckbs_sumsq_obj | Affine Residual Sum of Squares Objective |
| ckbs_L2L1_obj | Affine Least Squares with Robust L1 Objective |
| ckbs_sumsq_grad | Affine Residual Sum of Squares Gradient |
| ckbs_process_grad | Affine Residual Process Sum of Squares Gradient |
| ckbs_sumsq_hes | Affine Residual Sum of Squares Hessian |
| ckbs_process_hes | Affine Process Residual Sum of Squares Hessian |
| ckbs_tridiag_solve | Symmetric Block Tridiagonal Algorithm |
| ckbs_tridiag_solve_b | Symmetric Block Tridiagonal Algorithm (Backward version) |
| ckbs_tridiag_solve_pcg | Symmetric Block Tridiagonal Algorithm (Conjugate Gradient version) |
| ckbs_newton_step | Affine Constrained Kalman Bucy Smoother Newton Step |
| ckbs_newton_step_L1 | Affine Robust L1 Kalman Bucy Smoother Newton Step |
| ckbs_kuhn_tucker | Compute Residual in Kuhn-Tucker Conditions |
| ckbs_kuhn_tucker_L1 | Compute Residual in Kuhn-Tucker Conditions for Robust L1 |