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With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.

copied from cf-staging / r-tmb
Type Size Name Uploaded Downloads Labels
conda 1.0 MB | osx-64/r-tmb-1.7.19-r40hd8a265e_0.tar.bz2  4 years and 26 days ago 245 main
conda 1004.6 kB | win-64/r-tmb-1.7.19-r40h399f8d5_0.tar.bz2  4 years and 26 days ago 924 main
conda 991.7 kB | win-64/r-tmb-1.7.19-r36h399f8d5_0.tar.bz2  4 years and 26 days ago 922 main
conda 1.0 MB | osx-64/r-tmb-1.7.19-r36hd8a265e_0.tar.bz2  4 years and 26 days ago 256 main
conda 1.0 MB | linux-64/r-tmb-1.7.19-r40h306847c_0.tar.bz2  4 years and 26 days ago 2686 main
conda 1.0 MB | linux-64/r-tmb-1.7.19-r36h306847c_0.tar.bz2  4 years and 26 days ago 2579 main

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