tcltk, tools, digest (>= 0.6.3), R.devices (>= 2.2.2), ascii,
markdown, knitr

stats, utils, tools, R.methodsS3 (>= 1.5.1), R.utils (>=
1.27.1)

stats, utils, tools, R.methodsS3 (>= 1.5.2), R.utils (>=
1.27.1)

c(person("Milan", "Bouchet-Valat", email="nalimilan@club.fr", role=c("aut", "cre")),
person("Gilles", "Bastin", email="gilles.bastin@sciencespo-grenoble.fr", role="aut"),
person("Antoine", "Chollet", email="antoine.chollet@eleve.ensai.fr", role="aut"))
stats, utils, graphics, testthat, wordcloud, igraph, stringi,
crayon, SnowballC, tm.plugin.factiva, tm.plugin.lexisnexis,
tm.plugin.europresse, tm.plugin.alceste
tm (>= 0.6), NLP, slam, FactoMineR, explor
An integrated solution to perform
a series of text mining tasks such as importing and cleaning a corpus, and
analyses like terms and documents counts, lexical summary, terms
co-occurrences and documents similarity measures, graphs of terms,
correspondence analysis and hierarchical clustering. Corpora can be imported
from spreadsheet-like files, directories of raw text files,
as well as from 'Dow Jones Factiva', 'LexisNexis', 'Europresse' and 'Alceste' files.
Milan Bouchet-Valat [aut, cre],
Gilles Bastin [aut],
Antoine Chollet [aut]

This package provides utility classes and methods useful when programming in R and developing R packages.

This package provides utility classes and methods useful
when programming in R and developing R packages.

This package provides utility methods useful when
programming and developing R packages.

This package provides utility methods useful when programming and developing R packages.

Utility functions useful when programming and developing R packages.

methods, utils, tools, R.methodsS3 (>= 1.7.0)

methods, utils, tools, R.methodsS3 (>= 1.8.0)

methods, utils, tools, R.methodsS3 (>= 1.8.1)

methods, utils, tools, R.methodsS3 (>= 1.7.1)

Estimation of R0 and real-time reproduction number from
epidemics
This package is designed to estimate reproduction numbers
for disease outbreak, based on incidence data. It implements
several documented methods. It is therefore possible to compare
estimations according to the methods used. Depending on the
methods requested by user, basic reproduction number (commonly
denoted as R0) or real-time reproduction number (referred to as
R(t)) is computed, along with a 95% Confidence Interval.
Plotting outputs will give different graphs depending on the
methods requested : basic reproductive number estimations will
only show the epidemic curve (collected data) and an adjusted
model, whereas real-time methods will also show the R(t)
variations throughout the outbreak time period. Sensitivity
analysis tools are also provided, and allow for investigating
effects of varying Generation Time distribution or time window
on estimates.