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Provides 'Scilab' 'n1qn1', or Quasi-Newton BFGS "qn" without constraints and 'qnbd' or Quasi-Newton BFGS with constraints. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. If the Hessian is near enough the truth in optimization it can speed up the optimization problem. Both algorithms are described in the 'Scilab' optimization documentation located at <http://www.scilab.org/content/download/250/1714/file/optimization_in_scilab.pdf>.

Type Size Name Uploaded Downloads Labels
conda 93.2 kB | win-64/r-n1qn1-6.0.1_3-r36h5b3a9a7_0.tar.bz2  4 years and 9 months ago 6 main
conda 99.3 kB | osx-64/r-n1qn1-6.0.1_3-r36hbe7ee20_0.tar.bz2  4 years and 9 months ago 5 main
conda 94.8 kB | linux-64/r-n1qn1-6.0.1_3-r36h80f5a37_0.tar.bz2  4 years and 9 months ago 5 main

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