Authors@R: c(person("Beilun", "Wang", role = c("aut", "cre"), email = "bw4mw@virginia.edu"), person("Yanjun", "Qi", role = "aut", email = "yanjun@virginia.edu"),person("Zhaoyang", "Wang", role = c("aut"), email = "zw4dn@virginia.edu"))
Packaged: 2018-07-03 19:28:20 UTC; Karen Chen

Title: Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)
Authors@R: person("Christopher", "Rackauckas", email = "me@chrisrackauckas.com", role = c("aut", "cre"))
Description: An interface to 'DifferentialEquations.jl' from the R programming language.
It has unique high performance methods for solving ordinary differential equations (ODE), stochastic differential equations (SDE),
delay differential equations (DDE), differential-algebraic equations (DAE), and more. Much of the functionality,
including features like adaptive time stepping in SDEs, are unique and allow for multiple orders of magnitude speedup over more common methods.
'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users.
SystemRequirements: Julia (>= 0.6.0), DifferentialEquations.jl
Author: Christopher Rackauckas [aut, cre]

Description: An interface to 'DifferentialEquations.jl' <http://docs.juliadiffeq.org/latest/> from the R programming language.

Description: An interface to 'DifferentialEquations.jl' <https://diffeq.sciml.ai/dev/> from the R programming language.
SystemRequirements: Julia (>= 1.5), DifferentialEquations.jl,

Authors@R: person("Christopher", "Rackauckas", email = "me@chrisrackauckas.com", role = c("aut", "cre", "cph"))
'diffeqr' attaches an R interface onto the package, allowing seamless use of this tooling by R users. For more information,
see Rackauckas and Nie (2017) <doi:10.5334/jors.151>.
Author: Christopher Rackauckas [aut, cre, cph]

Description: An algorithm based on graph theory tools to detect differentiation
problems. A differentiation problem occurs when aggregated
data are disseminated according to two different nomenclatures. By making the
difference for an additive variable X between an aggregate composed of categories
of the first nomenclature and an other aggregate, included in that first
aggregate, composed of categories of the second nomenclature,
it is sometimes possible to derive X on a small aggregate of records
which could then lead to a break of confidentiality.
The purpose of this package is to detect the set of aggregates composed of
categories of the first nomenclature which lead to a differentiation problem,
Imports: tidyverse, igraph, progress, Rcpp, sf, dplyr, Matrix,
Authors@R: c(person("Vianney", "Costemalle", email = "vianney.costemalle@insee.fr", role = c("aut", "cre")),person("Arlindo", "Dos Santos", email = "arlindo.dos.santos@insee.fr", role = "aut"),person("Francois", "Semecurbe", email = "francois.semecurbe@insee.fr", role = "aut"))