DESCRIPTION

Package: sdbmsABC
Title: Spectral density-based and measure preserving ABC for the stochastic Jansen and Rit neural mass model (JR-NMM). The package contains the numerical Strang splitting scheme for the synthetic data simulation via a structure-preserving method
Version: 0.1.0
Authors: Irene Tubikanec, Massimiliano Tamborrino
Maintainer: Massimiliano Tamborrino <massimiliano.tamborrino@jku.at>
Description: Sample code to generate the marginal posterior densities for the inference of theta=(sigma,mu,C) from
    the 6-dimensional JR-NMM (a Hamiltonian type SDE). The proposed algorithm is based on the combination of the 
    structure-preserving numerical Strang splitting scheme and the estimated invariant densities and invariant spectral
    densities as proposed summary statistics. The chosen distance is a weighted sum of the areas between these curves and
    the corresponding curves estimated from the observed dataset. We refer to the paper on
    arXiv:1903.01138v1 for more information
Depends: R (>= 3.4.4), Rcpp,RcppEigen,BH,doParallel,doRNG,foreach,pkgbuild,doSNOW,
Imports: Rcpp (>= 0.11.6),RcppEigen,BH
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp,RcppEigen,BH
RoxygenNote: 6.1.1.9000