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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimate_R_plots.R
\name{estimate_R_plots}
\alias{estimate_R_plots}
\title{Wrapper for plot.estimate_R}
\usage{
estimate_R_plots(..., legend = FALSE)
}
\arguments{
\item{...}{Arguments of
\code{\link{plot.estimate_R}}, but in addition,
parameter \code{x} can be a objects of class \code{estimate_R} (obtained as
outputs of functions \code{\link{estimate_R}} or
\code{\link{wallinga_teunis}}.
If \code{x} is a list, and \code{what='R'} or \code{what='all'},
all estimates of R are plotted on a
single graph. This will only work if all the \code{estimate_R} objects in
the list were computed using the same \code{config$t_start} and
\code{config$t_end}}
\item{legend}{A boolean (TRUE by default) governing the presence / absence of
legends on the plots}
}
\value{
a plot (if \code{what = "incid"}, \code{"R"}, or \code{"SI"}) or a
\code{\link[grid]{grob}} object (if \code{what = "all"}).
}
\description{
This wrapper has been created so that several \code{estimate_R} objects can
be plotted at the same time.
}
\examples{
## load data on pandemic flu in a school in 2009
data("Flu2009")
#### COMPARE THE INSTANTANEOUS AND CASE REPRODUCTION NUMBERS ####
## estimate the instantaneous reproduction number
## (method "non_parametric_si")
R_instantaneous <- estimate_R(Flu2009$incidence,
method = "non_parametric_si",
config = list(t_start = seq(2, 26),
t_end = seq(8, 32),
si_distr = Flu2009$si_distr
)
)
## estimate the case reproduction number
R_case <- wallinga_teunis(Flu2009$incidence,
method = "non_parametric_si",
config = list(t_start = seq(2, 26),
t_end = seq(8, 32),
si_distr = Flu2009$si_distr
)
)
## visualise R estimates on the same plot
estimate_R_plots(list(R_instantaneous, R_case), what = "R",
options_R = list(col = c("blue", "red")), legend = TRUE)
#### COMPARE THE INSTANTANEOUS R ON SLIDING WEEKLY OR BIWEEKLY WINDOWS ####
R_weekly <- estimate_R(Flu2009$incidence,
method = "non_parametric_si",
config = list(t_start = seq(9, 26),
t_end = seq(15, 32),
si_distr = Flu2009$si_distr
)
)
R_biweekly <- estimate_R(Flu2009$incidence,
method = "non_parametric_si",
config = list(t_start = seq(2, 19),
t_end = seq(15, 32),
si_distr = Flu2009$si_distr
)
)
## visualise R estimates on the same plot
estimate_R_plots(list(R_weekly, R_biweekly), what = "R",
options_R = list(col = c("blue", "red")), legend = TRUE)
}
\seealso{
\code{\link{plot.estimate_R}}
}
\author{
Anne Cori, Zhian Kamvar
}
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