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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 995.0 kB | win-64/r-tmb-1.7.18-r36hb8e368e_0.tar.bz2  4 years and 7 months ago 1034 main
conda 989.4 kB | win-64/r-tmb-1.7.18-r40hb8e368e_0.tar.bz2  4 years and 7 months ago 1026 main
conda 1.0 MB | osx-64/r-tmb-1.7.18-r36hdfb1349_0.tar.bz2  4 years and 7 months ago 331 main
conda 1.0 MB | osx-64/r-tmb-1.7.18-r40hdfb1349_0.tar.bz2  4 years and 7 months ago 328 main
conda 1.0 MB | linux-64/r-tmb-1.7.18-r40h51c796c_0.tar.bz2  4 years and 7 months ago 3260 main
conda 1000.4 kB | linux-64/r-tmb-1.7.18-r36h51c796c_0.tar.bz2  4 years and 7 months ago 9304 main

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