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stk_param_relik uses a combination of "filtering matrix" (obtained using QR) and a Cholesky factorizations of the filtered covariance matrix. This computational approach could/should be encapsulated in a class similar to (but distinct from) stk_kreq_qr.
Other parts of the toolbox work with a different computational approach, encapsulated in stk_kreq_qr (namlely, a QR factorization of the "kriging matrix"). Why not use the same technique in stk_param_relik as well? For instance, it should be possible to compute the restricted likelihood from an stk_model_gpposterior object very quickly (since everything has been pre-computed).
Ideally, once both approaches (and possibly others !) have been properly encapsulated, it should be possible to switch transparently between them for all computations in the toolbox—likelihoods and predictions.
stk_param_relik
uses a combination of "filtering matrix" (obtained using QR) and a Cholesky factorizations of the filtered covariance matrix. This computational approach could/should be encapsulated in a class similar to (but distinct from)stk_kreq_qr
.Other parts of the toolbox work with a different computational approach, encapsulated in
stk_kreq_qr
(namlely, a QR factorization of the "kriging matrix"). Why not use the same technique instk_param_relik
as well? For instance, it should be possible to compute the restricted likelihood from anstk_model_gpposterior
object very quickly (since everything has been pre-computed).Ideally, once both approaches (and possibly others !) have been properly encapsulated, it should be possible to switch transparently between them for all computations in the toolbox—likelihoods and predictions.
(ref orginal ticket on SourceForge: https://sourceforge.net/p/kriging/tickets/5/)
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