Update about.html

[Rnaught] / man / id.Rd

diff --git a/man/id.Rd b/man/id.Rd
index 1d32c50b67dcefa7a295cbf2d9ac394856963eaf..27f49d0dfa72e7782a6cfe8e9b1c51ec89664f2b 100644 (file)
--- a/man/id.Rd
+++ b/man/id.Rd
@@ -1,22 +1,23 @@
 % Generated by roxygen2: do not edit by hand
 % Generated by roxygen2: do not edit by hand

-% Please edit documentation in R/ID.R
-\name{ID}
-\alias{ID}
-\title{ID method}
+% Please edit documentation in R/id.R
+\name{id}
+\alias{id}
+\title{Incidence Decay (ID)}

 \usage{
 \usage{

-ID(NT, mu)
+id(cases, mu)

 }
 \arguments{
 }
 \arguments{

-\item{NT}{Vector of case counts.}
+\item{cases}{Vector of case counts. The vector must be non-empty and only
+contain positive integers.}

 
 

-\item{mu}{Mean of the serial distribution. This needs to match case counts
-in time units. For example, if case counts are weekly and the
-serial distribution has a mean of seven days, then \code{mu} should
-be set to one. If case counts are daily and the serial distribution
-has a mean of seven days, then \code{mu} should be set to seven.}
+\item{mu}{Mean of the serial distribution. This must be a positive number.
+The value should match the case counts in time units. For example, if case
+counts are weekly and the serial distribution has a mean of seven days,
+then \code{mu} should be set to \code{1}. If case counts are daily and the serial
+distribution has a mean of seven days, then \code{mu} should be set to \code{7}.}

 }
 \value{
 }
 \value{

-\code{ID} returns a single value, the estimate of R0.
+An estimate of the basic reproduction number (R0).

 }
 \description{
 This function implements a least squares estimation method of R0 due to
 }
 \description{
 This function implements a least squares estimation method of R0 due to


@@ -25,7 +26,7 @@ Fisman et al. (PloS One, 2013). See details for implementation notes.
 \details{
 The method is based on a straightforward incidence decay model. The estimate
 of R0 is the value which minimizes the sum of squares between observed case
 \details{
 The method is based on a straightforward incidence decay model. The estimate
 of R0 is the value which minimizes the sum of squares between observed case

-counts and cases counts 'expected' under the model.
+counts and cases counts expected under the model.

 
 This method is based on an approximation of the SIR model, which is most
 valid at the beginning of an epidemic. The method assumes that the mean of
 
 This method is based on an approximation of the SIR model, which is most
 valid at the beginning of an epidemic. The method assumes that the mean of


@@ -35,13 +36,18 @@ is strongly recommended. Users should be careful about units of time (e.g.,
 are counts observed daily or weekly?) when implementing.
 }
 \examples{
 are counts observed daily or weekly?) when implementing.
 }
 \examples{

-# Weekly data:
-NT <- c(1, 4, 10, 5, 3, 4, 19, 3, 3, 14, 4)
+# Weekly data.
+cases <- c(1, 4, 10, 5, 3, 4, 19, 3, 3, 14, 4)

 
 # Obtain R0 when the serial distribution has a mean of five days.
 
 # Obtain R0 when the serial distribution has a mean of five days.

-ID(NT, mu = 5 / 7)
+id(cases, mu = 5 / 7)

 
 # Obtain R0 when the serial distribution has a mean of three days.
 
 # Obtain R0 when the serial distribution has a mean of three days.

-ID(NT, mu = 3 / 7)
-
+id(cases, mu = 3 / 7)
+}
+\references{
+\href{https://doi.org/10.1371/journal.pone.0083622}{Fisman et al. (PloS One, 2013)}
+}
+\seealso{
+\code{\link[=idea]{idea()}} for a similar method.

 }
 }