shinyjs, stats, tidyr, table1, data.table, utils
ggrepel, patchwork, bayestestR, plotly, scales, shinyAce, Rcpp,

Imports: colourpicker, dplyr, egg, grid, ggplot2 (>= 3.3.2), markdown,
shiny, shinyjs, shinymeta, stats, tidyr, table1, utils
ggrepel, ggstance, patchwork, plotly, scales, shinyAce, Rcpp,

Imports: colourpicker, egg, grid, ggplot2 (>= 3.3.2), shiny, stats,
Suggests: markdown, dplyr, tidyr, shinyjs, shinymeta, table1, clipr,
formatR, MASS, knitr, rmarkdown, mrgsolve, GGally, ggridges,

Title: Test for Equality of Covariance Matrices
email = "maxime.turgeon@mail.mcgill.ca", role = c("aut", "cre"))
Description: Computes p-values using the largest root test using
an approximation to the null distribution by Johnstone (2008) <DOI:10.1214/08-AOS605>.

Title: Covfefy Any Word, Sentence or Speech
Description: Converts any word, sentence or speech into Trump's infamous
Packaged: 2017-06-06 14:32:27 UTC; mkirchner

Title: Sparse Covariance Matrix Estimation
Description: Direct sparse covariance matrix estimation via the covariance graphical lasso by Bien, Tibshirani (2011) <doi:10.1093/biomet/asr054> using the fast coordinate descent algorithm of Wang (2014) <doi:10.1007/s11222-013-9385-5>.
Authors@R: c(person("Michael", "Fop", role = c("aut", "cre"),
Author: Michael Fop [aut, cre] (<https://orcid.org/0000-0003-3936-2757>),

Title: Load and Analyze Live Data from the CoViD-19 Pandemic
Description: Load and analyze updated time series worldwide data of reported cases for the Novel CoronaVirus Disease (CoViD-19) from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository <https://github.com/CSSEGISandData/COVID-19>. The datasets are available in two main modalities, as a time series sequences and aggregated for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread.
Imports: ape, plotly, htmlwidgets, deSolve, gplots, pheatmap