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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 1.2 MB | linux-ppc64le/r-tmb-1.9.10-r43hfc38db2_0.conda  1 year and 2 months ago 284 main
conda 1.1 MB | win-64/r-tmb-1.9.10-r41h78deb2a_0.conda  1 year and 3 months ago 566 main
conda 1.1 MB | osx-64/r-tmb-1.9.10-r42h86c1099_0.conda  1 year and 3 months ago 470 main
conda 1.1 MB | osx-64/r-tmb-1.9.10-r43h86c1099_0.conda  1 year and 3 months ago 491 main
conda 1.2 MB | linux-ppc64le/r-tmb-1.9.10-r42hfc38db2_0.conda  1 year and 3 months ago 265 main
conda 1.1 MB | linux-64/r-tmb-1.9.10-r43h08d816e_0.conda  1 year and 3 months ago 1719 main
conda 1.1 MB | linux-64/r-tmb-1.9.10-r42h08d816e_0.conda  1 year and 3 months ago 1642 main
conda 1.1 MB | linux-aarch64/r-tmb-1.9.10-r42h003610b_0.conda  1 year and 3 months ago 262 main
conda 1.1 MB | linux-aarch64/r-tmb-1.9.10-r43h003610b_0.conda  1 year and 3 months ago 269 main

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