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.
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curl https://depscope.dev/api/check/conda/r-tmbFirst published · 2020-07-23 18:16:35.306000+00:00
Last updated · 2026-03-23 11:53:02.623000+00:00