NAME

datasets

The Rcpp package provides R functions as well as a C++
        library which facilitate the integration of R and C++.

 R data types (SEXP) are matched to C++ objects in a class hierarchy.
        All R types are supported (vectors, functions, environment, etc
        ...)  and each type is mapped to a dedicated class. For
        example, numeric vectors are represented as instances of the
        Rcpp::NumericVector class, environments are represented as
        instances of Rcpp::Environment, functions are represented as
        Rcpp::Function, etc ... The "Rcpp-introduction" vignette
        provides a good entry point to Rcpp.

 Conversion from C++ to R and back is driven by the templates Rcpp::wrap
        and Rcpp::as which are highly flexible and extensible, as
        documented in the "Rcpp-extending" vignette.

 Rcpp also provides Rcpp modules, a framework that allows exposing C++
        functions and classes to the R level. The "Rcpp-modules"
        vignette details the current set of features of Rcpp-modules.

 Rcpp includes a concept called Rcpp sugar that brings many R functions
        into C++. Sugar takes advantage of lazy evaluation and
        expression templates to achieve great performance while
        exposing a syntax that is much nicer to use than the equivalent
        low-level loop code. The "Rcpp-sugar" vignette gives an
        overview of the feature.

 Several examples are included, and over 800 unit tests in over 360 unit
        test functions provide additional usage examples.

 An earlier version of Rcpp, containing what we now call the 'classic
        Rcpp API' was written during 2005 and 2006 by Dominick Samperi.
        This code has been factored out of Rcpp into the package
        RcppClassic, and it is still available for code relying on the
        older interface. New development should always use this Rcpp
        package instead.

NAME: Rcpp module:

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Examples