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-post-staging / r-tmb| Label | Latest Version |
|---|---|
| main | 1.9.19 |
| cf201901 | 1.7.14 |
| cf202003 | 1.7.16 |
| gcc7 | 1.7.14 |
