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  1. Data Management
  2. DM-20887

Cleanup jointcal dmtn-036 section 4.3

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      Having spent some time with Nocedal & Wright's "Numerical Optimization 2nd ed.", I'd like to rework the text in section 4.3 of the jointcal paper to better reflect how a least-squares style optimization problem is described in that book. This may or may not result in a change of notation, but it should allow simplification and clarification of the descriptions of how the Jacobian and Hessian matrices are derived, plus a better description of why an Cholesky LDL factorization is a good choice. I think that rewriting this text would be a good start on rethinking how we go about outlier removal and what our available choices are for optimization algorithms.

      Chapter 10 and some of chapter 3 are particularly useful in thinking about the classes algorithm that we can apply.

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          Parejkoj John Parejko added a comment -

          Noting a couple of things in particular before I return the book to the library:

          • compare equation 10.47 with equations 3-7 in the current (2018-07-13) version of dmtn-036.
          • look at Seber & Wild, "Nonlinear Regression" 1989 (Wiley & Sons) for more about minimizing functions of the form r^T*W*r for symmetric weights W.
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          Parejkoj John Parejko added a comment - Noting a couple of things in particular before I return the book to the library: compare equation 10.47 with equations 3-7 in the current (2018-07-13) version of dmtn-036. look at Seber & Wild, "Nonlinear Regression" 1989 (Wiley & Sons) for more about minimizing functions of the form r^T*W*r for symmetric weights W.

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            • Assignee:
              Parejkoj John Parejko
              Reporter:
              Parejkoj John Parejko
              Watchers:
              Jim Bosch, John Parejko, John Swinbank
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