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Data Structure and Manipulations Tool for Host and Viral Population

Statistical Methods for Inferring Transmissions of Infectious Diseases from deep sequencing data (SMITID). It allow sequence-space-time host and viral population data storage, indexation and querying.

Functions to Make Surveys Processing Easier

Set of functions to make the processing and analysis of surveys easier : interactive shiny apps and addins for data recoding, contingency tables, dataset metadata handling, and several convenience functions.

Adaptation of Virtual Twins Method from Jared Foster

Research of subgroups in random clinical trials with binary outcome and two treatments groups. This is an adaptation of the Jared Foster method (< https://www.ncbi.nlm.nih.gov/pubmed/21815180>).

Estimation and Simulation for PDMPs

This package deals with the estimation of the jump rate for piecewise-deterministic Markov processes (PDMPs), from only one observation of the process within a long time. The main functions provide an estimate of this function. The state space may be discrete or continuous. The associated paper has been published in Scandinavian Journal of Statistics and is given in references. Other functions provide a method to simulate random variables from their (conditional) hazard rate, and then to simulate PDMPs.

Inference Using Simulation

Implements functions for simulation-based inference. In particular, implements functions to perform likelihood inference from data summaries whose distributions are simulated (Rousset et al. 2017

Population Genetic Data Analysis Using Genepop

Makes the Genepop software available in R. This software implements a mixture of traditional population genetic methods and some more focused developments: it computes exact tests for Hardy-Weinberg equilibrium, for population differentiation and for genotypic disequilibrium among pairs of loci; it computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc.; and it performs analyses of isolation by distance from pairwise comparisons of individuals or population samples.

GPL Palettes Copied from 'Gimp' and 'Inkscape'

A set of palettes imported from 'Gimp' distributed under GPL3 (< https://www.gimp.org/about/COPYING>), and 'Inkscape' distributed under GPL2 (< https://inkscape.org/about/license/>).

Rcpp bindings for the Boost Date_Time library

This package provides R with access to Boost Date_Time functionality by using Rcpp modules. Functionality from Boost Date_Time for dates, durations (both for days and datetimes), timezones, and posix time ("ptime") is provided. The posix time implementation can support high-resolution of up to nano-second precision by using 96 bits (instead of R's 64) to present a ptime object.

C++ Classes to Embed R in C++ Applications

C++ classes to embed R in 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. d Numerous examples are provided in the eight 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') and 'eigen' (for 'RInside' use with 'RcppEigen'). 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.

Examples using 'Rcpp' to Interface R and C++

Examples for Seamless R and C++ integration The 'Rcpp' package contains a C++ library that facilitates the integration of R and C++ in various ways. This package provides some usage examples. Note that the documentation in this package currently does not cover all the features in the package. It is not even close. On the other hand, the site < http://gallery.rcpp.org> is regrouping a large number of examples for 'Rcpp'.