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-tmbLabel | Latest Version |
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main | 1.9.15 |
cf201901 | 1.7.14 |
cf202003 | 1.7.16 |
gcc7 | 1.7.14 |