Title: Run Reports, Models, and Scripts from a Mobile Device
Description: A framework for interacting with
R modules such as Reports, Models, and Scripts from a mobile device.
The framework allows you to list available modules and select a
module of interest using a basic e-mail interface. After
selecting a specific module, you can either run it as is or
provide input via the e-mail interface. After parsing your
request, R will send the results back to your mobile device.
Imports: knitr, kableExtra, ggplot2, XML, plyr, utils, yaml, mailR

Description: Some canned plots and functions designed for the mobilize
project.  Designed to be called remotely.
Depends: R (>= 2.14), stats, methods, Ohmage
Imports: ggplot2, wordcloud, Ohmage, reshape2

Description: Some canned plots and functions designed for the mobilize project.

Title: Mode Estimation, Even in the Multimodal Case
person("Jerome", "Collet", role = c("aut", "cre"),
Description: Function ModEstM() is the only one of this package, it estimates the modes of an empirical univariate distribution. It relies on the stats::density() function, even for input control. Due to very good performance of the density estimation, computation time is not an issue. The multiple modes are handled using dplyr::group_by(). For conditions and rates of convergences, see Eddy (1980) <doi:10.1214/aos/1176345080>.

Title: Statistical Modelling in Action with R
Imports: stats, boot, ggplot2, BioStatR, jmuOutlier, ellipse, hypergeo,
person(given = "Emmanuelle", family= "Claeys", role = c("aut"), email = "emmanuelle.claeys@unistra.fr"),
Description: Datasets and functions for the book "Modélisation statistique par la pratique avec R", F. Bertrand, E. Claeys and M. Maumy-Bertrand (2019, ISBN:9782100793525, Dunod, Paris). The first chapter of the book is dedicated to an introduction to the R statistical software. The second chapter deals with correlation analysis: Pearson, Spearman and Kendall simple, multiple and partial correlation coefficients. New wrapper functions for permutation tests or bootstrap of matrices of correlation are provided with the package. The third chapter is dedicated to data exploration with factorial analyses (PCA, CA, MCA, MDA) and clustering. The fourth chapter is dedicated to regression analysis: fitting and model diagnostics are detailed. The exercises focus on covariance analysis, logistic regression, Poisson regression, two-way analysis of variance for fixed or random factors. Various example datasets are shipped with the package: for instance on pokemon, world of warcraft, house tasks or food nutrition analyses.