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
conda install conda-forge::r-tmbconda install conda-forge/label/cf201901::r-tmbconda install conda-forge/label/cf202003::r-tmbconda install conda-forge/label/gcc7::r-tmb