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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-1.9.4-r41h78deb2a_1.conda  2 years and 2 months ago 757 main
conda 1.1 MB | osx-64/r-tmb-1.9.4-r42he9b8800_1.conda  2 years and 2 months ago 495 main
conda 1.1 MB | osx-64/r-tmb-1.9.4-r43he9b8800_1.conda  2 years and 2 months ago 471 main
conda 1.1 MB | linux-64/r-tmb-1.9.4-r43h08d816e_1.conda  2 years and 2 months ago 2058 main
conda 1.1 MB | linux-64/r-tmb-1.9.4-r42h08d816e_1.conda  2 years and 2 months ago 2020 main
conda 1.1 MB | osx-64/r-tmb-1.9.4-r41hf5e6a41_0.conda  2 years and 3 months ago 447 main
conda 1.0 MB | win-64/r-tmb-1.9.4-r41h78deb2a_0.conda  2 years and 3 months ago 783 main
conda 1.1 MB | osx-64/r-tmb-1.9.4-r42hf5e6a41_0.conda  2 years and 3 months ago 468 main
conda 1.1 MB | linux-64/r-tmb-1.9.4-r42h358215d_0.conda  2 years and 3 months ago 2175 main
conda 1.1 MB | linux-64/r-tmb-1.9.4-r41h358215d_0.conda  2 years and 3 months ago 2733 main

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