RStudio Addin for Searching Packages in CRAN Database Based on Keywords (CRANsearcher)
One of the strengths of R is its vast package ecosystem. Indeed, R packages extend from visualization to Bayesian inference and from spatial analyses to pharmacokinetics (<https://…/> ). There is probably not an area of quantitative research that isn’t represented by at least one R package. At the time of this writing, there are more than 10,000 active CRAN packages. Because of this massive ecosystem, it is important to have tools to search and learn about packages related to your personal R needs. For this reason, we developed an RStudio addin capable of searching available CRAN packages directly within RStudio.

Parses Web Pages using Postlight Mercury (postlightmercury)
This is a wrapper for the Mercury Parser API. The Mercury Parser is a single API endpoint that takes a URL and gives you back the content reliably and easily. With just one API request, Mercury takes any web article and returns only the relevant content — headline, author, body text, relevant images and more — free from any clutter. It’s reliable, easy-to-use and free. See the webpage here: <https://…/>.

Analysis of Time-Ordered Event Data with Missed Observations (intRvals)
Calculates event rates and compares means and variances of groups of interval data corrected for missed arrival observations.

Utilities for Delaying Function Execution (later)
Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied.

Simplification of Surface Triangular Meshes with Associated Distributed Data (meshsimp)
Iterative simplification strategy for surface triangular meshes (2.5D meshes) with associated data. Each iteration corresponds to an edge collapse where the selection of the edge to contract is driven by a cost functional that depends both on the geometry of the mesh than on the distribution of the data locations over the mesh. The library can handle both zero and higher genus surfaces. The package has been designed to be fully compatible with the R package ‘fdaPDE’, which implements regression models with partial differential regularizations, making use of the Finite Element Method. In the future, the functionalities provided by the current package may be directly integrated into ‘fdaPDE’.