From 80df3ed7a280f86a3b9b5443309487d428f4fe95 Mon Sep 17 00:00:00 2001
From: Naeem Model <me@nmode.ca>
Date: Thu, 29 Jun 2023 23:47:01 +0000
Subject: Re-style code and enforce 80 character line limit

---
 R/IDEA.R | 72 +++++++++++++++++++++++++++++++---------------------------------
 1 file changed, 35 insertions(+), 37 deletions(-)

(limited to 'R/IDEA.R')

diff --git a/R/IDEA.R b/R/IDEA.R
index 854acd7..53fa653 100644
--- a/R/IDEA.R
+++ b/R/IDEA.R
@@ -1,58 +1,56 @@
 #' 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 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
+#' 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.
+#' 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.
+#' @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                             ##
-#' ## ===================================================== ##
-#'
+#' # 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      ##
-#' ## ========================================================= ##
+#' # Obtain R0 when the serial distribution has a mean of five days.
+#' IDEA(NT, mu = 5 / 7)
 #'
-#' IDEA(NT=NT[1:5], mu=5/7) # serial distribution has mean of five days
+#' # Obtain R0 when the serial distribution has a mean of three days.
+#' IDEA(NT, mu = 3 / 7)
 #'
 #' @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
+  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)
+    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)
+    IDEA1 <- sum(y2) * sum(y1) - sum(s) * sum(y3)
+    IDEA2 <- TT * sum(y2) - sum(s)^2
+    IDEA <- exp(IDEA1 / IDEA2)
 
-        return(IDEA)
-    }
+    return(IDEA)
+  }
 }
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