person(given = "Arsenij", family = "Ustjanzew", email = "arsenij.ustjanzew@gmail.com", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-1014-4521")),
Author: Arsenij Ustjanzew [aut, cre, cph]

Imports: magrittr, knitr, flexdashboard, assertive.sets,
Suggests: switchr, plotly, BiocStyle, testthat, ComplexHeatmap, digest,
ggplot2, gt, kableExtra, forcats, leaflet
'colormap.R' 'get_set.R' 'i2dash-pkg.R' 'pages.R' 'reexports.R'

Title: Functions to Work with 'incidence2' Objects
person("Tim", "Taylor", role = c("aut", "cre"), email = "tim.taylor@hiddenelephants.co.uk",
person("Thibaut", "Jombart", role = c("aut"), email = "thibautjombart@gmail.com"),
person("Zhian N.", "Kamvar", role = "aut", email = "zkamvar@gmail.com",
Description: Provides functions to work with 'incidence2' objects, including a
simplified interface for trend fitting and peak estimation. This package is
part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for
Imports: utils, stats, MASS, incidence2, trending, dplyr, tibble,
Suggests: testthat, outbreaks, knitr, rmarkdown, covr

person("Thibaut", "Jombart", role = c("aut"), email = "thibautjombart@gmail.com")
Imports: utils, stats, incidence2 (>= 1.0.0), trending, dplyr, tibble,
rlang, tidyr, vctrs, ellipsis, ggplot2, data.table, tidyselect

Imports: utils, stats, incidence2 (>= 1.2.0), trending, dplyr, tibble,

Title: Irregularly Observed Autoregressive Models
person("Elorrieta", "Felipe", email = "felipe.elorrieta@usach.cl", role = c("aut","cre")),
person("Ojeda", "Cesar", email = "cesar.ojeda@correounivalle.edu.co", role = "aut"),
person("Eyheramendy", "Susana", email = "susana.eyheramendy@gmail.com", role = "aut"),
person("Palma", "Wilfredo", email = "wilfredo.palma@gmail.com", role = "aut"))
Description: Data sets, functions and scripts with examples to implement autoregressive models for irregularly observed time series. The models available in this package are the irregular autoregressive model (Eyheramendy et al.(2018) <doi:10.1093/mnras/sty2487>), the complex irregular autoregressive model (Elorrieta et al.(2019) <doi:10.1051/0004-6361/201935560>) and the bivariate irregular autoregressive model.