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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 1.1 MB | win-64/r-tmb-1.9.12-r41h3c88c7c_0.conda  8 months and 11 days ago 548 main
conda 1.2 MB | linux-ppc64le/r-tmb-1.9.12-r42h795cbc2_0.conda  8 months and 11 days ago 205 main
conda 1.2 MB | osx-64/r-tmb-1.9.12-r42h6a638e2_0.conda  8 months and 11 days ago 446 main
conda 1.2 MB | osx-64/r-tmb-1.9.12-r43h6a638e2_0.conda  8 months and 11 days ago 421 main
conda 1.1 MB | linux-aarch64/r-tmb-1.9.12-r43hd38cb5a_0.conda  8 months and 11 days ago 228 main
conda 1.1 MB | linux-aarch64/r-tmb-1.9.12-r42hd38cb5a_0.conda  8 months and 11 days ago 235 main
conda 1.2 MB | linux-64/r-tmb-1.9.12-r43h58a4165_0.conda  8 months and 11 days ago 1228 main
conda 1.1 MB | linux-64/r-tmb-1.9.12-r42h58a4165_0.conda  8 months and 11 days ago 1152 main

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