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[Rnaught] / R / IDEA.R

diff --git a/R/IDEA.R b/R/IDEA.R
index 20a94016707747120b5e795ca6bd19af00db6b4f..854acd7af108903da248048d34ee6ae20de3a81d 100644 (file)
--- a/R/IDEA.R
+++ b/R/IDEA.R
@@ -1,58 +1,58 @@
-#' IDEA method\r
-#'\r
-#' This function implements a least squares estimation method of R0 due to Fisman et al. (PloS One, 2013).\r
-#' See details for implementation notes.\r
-#'\r
-#' This method is closely related to that implemented in \code{ID}. The method is based on an incidence decay model.\r
-#' The estimate of R0 is the value which minimizes the sum of squares between observed case counts and cases counts\r
-#' expected under the model.\r
-#'\r
-#' This method is based on an approximation of the SIR model, which is most valid at the beginning of an epidemic.\r
-#' The method assumes that the mean of the serial distribution (sometimes called the serial interval) is known.\r
-#' The final estimate can be quite sensitive to this value, so sensitivity testing is strongly recommended.\r
-#' Users should be careful about units of time (e.g., are counts observed daily or weekly?) when implementing.\r
-#'\r
-#' @param NT Vector of case counts.\r
-#' @param mu Mean of the serial distribution. This needs to match case counts in time units. For example, if case counts\r
-#'           are weekly and the serial distribution has a mean of seven days, then \code{mu} should be set to one. If case\r
-#'           counts are daily and the serial distribution has a mean of seven days, then \code{mu} should be set to seven.\r
-#'\r
-#' @return \code{IDEA} returns a single value, the estimate of R0.\r
-#'\r
-#' @examples\r
-#' ## ===================================================== ##\r
-#' ## Illustrate on weekly data                             ##\r
-#' ## ===================================================== ##\r
-#'\r
-#' NT <- c(1, 4, 10, 5, 3, 4, 19, 3, 3, 14, 4)\r
-#' ## obtain Rhat when serial distribution has mean of five days\r
-#' IDEA(NT=NT, mu=5/7)\r
-#' ## obtain Rhat when serial distribution has mean of three days\r
-#' IDEA(NT=NT, mu=3/7)\r
-#'\r
-#' ## ========================================================= ##\r
-#' ## Compute Rhat using only the first five weeks of data      ##\r
-#' ## ========================================================= ##\r
-#'\r
-#' IDEA(NT=NT[1:5], mu=5/7) # serial distribution has mean of five days\r
-#'\r
-#' @export\r
-IDEA <- function(NT, mu) {\r
-    if (length(NT) < 2)\r
-        print("Warning: length of NT should be at least two.")\r
-    else {\r
-        NT <- as.numeric(NT)\r
-        TT <- length(NT)\r
-        s <- (1:TT) / mu\r
-\r
-        y1 <- log(NT) / s\r
-        y2 <- s^2\r
-        y3 <- log(NT)\r
-\r
-        IDEA1 <- sum(y2) * sum(y1) - sum(s) * sum(y3)\r
-        IDEA2 <- TT * sum(y2) - sum(s)^2\r
-        IDEA <- exp(IDEA1 / IDEA2)\r
-\r
-        return(IDEA)\r
-    }\r
-}\r
+#' IDEA method
+#'
+#' This function implements a least squares estimation method of R0 due to Fisman et al. (PloS One, 2013).
+#' See details for implementation notes.
+#'
+#' This method is closely related to that implemented in \code{ID}. The method is based on an 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.
+#'
+#' 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 the serial distribution (sometimes called the serial interval) is known.
+#' The final estimate can be quite sensitive to this value, so sensitivity testing is strongly recommended.
+#' Users should be careful about units of time (e.g., are counts observed daily or weekly?) when implementing.
+#'
+#' @param NT Vector of case counts.
+#' @param 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.
+#'
+#' @return \code{IDEA} returns a single value, the estimate of R0.
+#'
+#' @examples
+#' ## ===================================================== ##
+#' ## Illustrate on weekly data                             ##
+#' ## ===================================================== ##
+#'
+#' NT <- c(1, 4, 10, 5, 3, 4, 19, 3, 3, 14, 4)
+#' ## obtain Rhat when serial distribution has mean of five days
+#' IDEA(NT=NT, mu=5/7)
+#' ## obtain Rhat when serial distribution has mean of three days
+#' IDEA(NT=NT, mu=3/7)
+#'
+#' ## ========================================================= ##
+#' ## Compute Rhat using only the first five weeks of data      ##
+#' ## ========================================================= ##
+#'
+#' IDEA(NT=NT[1:5], mu=5/7) # serial distribution has mean of five days
+#'
+#' @export
+IDEA <- function(NT, mu) {
+    if (length(NT) < 2)
+        print("Warning: length of NT should be at least two.")
+    else {
+        NT <- as.numeric(NT)
+        TT <- length(NT)
+        s <- (1:TT) / mu
+
+        y1 <- log(NT) / s
+        y2 <- s^2
+        y3 <- log(NT)
+
+        IDEA1 <- sum(y2) * sum(y1) - sum(s) * sum(y3)
+        IDEA2 <- TT * sum(y2) - sum(s)^2
+        IDEA <- exp(IDEA1 / IDEA2)
+
+        return(IDEA)
+    }
+}