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copied!<p>@jbremnant: That's right. Rcpp classes implement something close to the RAII pattern. When an Rcpp object is created, the constructor takes appropriate measures to ensure the underlying R object (SEXP) is protected from the garbage collector. The destructor withdraws the protection. This is explained in the <a href="http://cran.r-project.org/web/packages/Rcpp/vignettes/Rcpp-introduction.pdf" rel="noreferrer">Rcpp-intrduction</a> vignette. The underlying implementation relies on the R API functions <strong>R_PreserveObject</strong> and <strong>R_ReleaseObject</strong></p> <p>There is indeed performance penalty due to C++ encapsulation. We try to keep this at a minimum with inlining, etc ... The penalty is small, and when you take into account the gain in terms of time it takes to write and maintain code, it is not that relevant. </p> <p>Calling R functions from the Rcpp class Function is slower than directly calling eval with the C api. This is because we take precautions and wrap the function call into a tryCatch block so that we capture R errors and promote them to C++ exceptions so that they can be dealt with using the standard try/catch in C++. </p> <p>Most people want to use vectors (specially NumericVector), and the penalty is very small with this class. The examples/ConvolveBenchmarks directory contains several variants of the notorious convolution function from R-exts and the vignette has benchmark results. It turns out that Rcpp makes it faster than the benchmark code that uses the R API. </p>

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