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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 matrixvector 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.
Package details 


Author  Kasper Kristensen [aut, cre, cph], Brad Bell [cph], Hans Skaug [ctb], Arni Magnusson [ctb], Casper Berg [ctb], Anders Nielsen [ctb], Martin Maechler [ctb], Theo Michelot [ctb], Mollie Brooks [ctb], Alex Forrence [ctb], Christoffer Moesgaard Albertsen [ctb], Cole Monnahan [ctb] 
Maintainer  Kasper Kristensen <kaskr@dtu.dk> 
License  GPL2 
Version  1.7.20 
URL  https://github.com/kaskr/adcomp/wiki 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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