Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 186 packages in 0.01 seconds

eurostat — by Leo Lahti, a year ago

Tools for Eurostat Open Data

Tools to download data from the Eurostat database < https://ec.europa.eu/eurostat> together with search and manipulation utilities.

BAT — by Pedro Cardoso, a year ago

Biodiversity Assessment Tools

Includes algorithms to assess alpha and beta diversity in all their dimensions (taxonomic, phylogenetic and functional). It allows performing a number of analyses based on species identities/abundances, phylogenetic/functional distances, trees, convex-hulls or kernel density n-dimensional hypervolumes depicting species relationships. Cardoso et al. (2015) .

abc.data — by Blum Michael, a year ago

Data Only: Tools for Approximate Bayesian Computation (ABC)

Contains data which are used by functions of the 'abc' package.

APIS — by Julien Roche, 3 months ago

Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents

Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions or Exclusion. The main functions of this package are the function APIS_2n(), APIS_3n() and launch_APIShiny(), which perform parentage assignment.

tinyProject — by Francois Guillem, 6 years ago

A Lightweight Template for Data Analysis Projects

Creates useful files and folders for data analysis projects and provides functions to manage data, scripts and output files. Also provides a project template for 'Rstudio'.

RCALI — by Jean-Francois Rey, 4 months ago

Calculation of the Integrated Flow of Particles Between Polygons

Calculate the flow of particles between polygons by two integration methods: integration by a cubature method and integration on a grid of points. Annie Bouvier, Kien Kieu, Kasia Adamczyk and Herve Monod (2009) .

RInside — by Dirk Eddelbuettel, 2 years ago

C++ Classes to Embed R in C++ (and C) Applications

C++ classes to embed R in C++ (and C) applications A C++ class providing the R interpreter is offered by this package making it easier to have "R inside" your C++ application. As R itself is embedded into your application, a shared library build of R is required. This works on Linux, OS X and even on Windows provided you use the same tools used to build R itself. Numerous examples are provided in the nine subdirectories of the examples/ directory of the installed package: standard, 'mpi' (for parallel computing), 'qt' (showing how to embed 'RInside' inside a Qt GUI application), 'wt' (showing how to build a "web-application" using the Wt toolkit), 'armadillo' (for 'RInside' use with 'RcppArmadillo'), 'eigen' (for 'RInside' use with 'RcppEigen'), and 'c_interface' for a basic C interface and 'Ruby' illustration. The examples use 'GNUmakefile(s)' with GNU extensions, so a GNU make is required (and will use the 'GNUmakefile' automatically). 'Doxygen'-generated documentation of the C++ classes is available at the 'RInside' website as well.

knitrProgressBar — by Robert M Flight, 7 months ago

Provides Progress Bars in 'knitr'

Provides a progress bar similar to 'dplyr' that can write progress out to a variety of locations, including stdout(), stderr(), or from file(). Useful when using 'knitr' or 'rmarkdown', and you still want to see progress of calculations in the terminal.

HSPOR — by Florine Greciet, 5 years ago

Hidden Smooth Polynomial Regression for Rupture Detection

Several functions that allow by different methods to infer a piecewise polynomial regression model under regularity constraints, namely continuity or differentiability of the link function. The implemented functions are either specific to data with two regimes, or generic for any number of regimes, which can be given by the user or learned by the algorithm. A paper describing all these methods will be submitted soon. The reference will be added to this file as soon as available.

briskaR — by Jean-Francois Rey, 3 years ago

Biological Risk Assessment

A spatio-temporal exposure-hazard model for assessing biological risk and impact. The model is based on stochastic geometry for describing the landscape and the exposed individuals, a dispersal kernel for the dissemination of contaminants, a set of tools to handle spatio-temporal dataframe and ecotoxicological equations. Walker E, Leclerc M, Rey JF, Beaudouin R, Soubeyrand S, and Messean A, (2017), A Spatio-Temporal Exposure-Hazard Model for Assessing Biological Risk and Impact, Risk Analysis, . Leclerc M, Walker E, Messean A, Soubeyrand S (2018), Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms, Science of the Total Environment, 624, 470-479.