From 89b299161cb5c0f5e1fc7bbe17181f931e443136 Mon Sep 17 00:00:00 2001
From: Degoot-AM <degoot@aims.ac.za>
Date: Thu, 20 Jun 2024 18:56:27 +0000
Subject: [PATCH] add peak estimation section

---
 episodes/describe-cases.Rmd | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/episodes/describe-cases.Rmd b/episodes/describe-cases.Rmd
index fd266a3e..d5e0884d 100644
--- a/episodes/describe-cases.Rmd
+++ b/episodes/describe-cases.Rmd
@@ -236,6 +236,26 @@ base::plot(cum_df) +
 
 Note that this function preserve grouping, i.e., if the the `incidence2` object contains groups, then it will accumlate the cases accrodingly. 
 
+##  Peak estimation
+
+One can estimate the peak --the time with highest number of recorded cases-- using `estimate_peak()` function from the {incidence2} package. 
+This function employs a bootstrapping method to determine the peak time.
+
+```{r, message=FALSE, warning=FALSE}
+peak <- incidence2::estimate_peak(
+  dialy_incidence_data,
+  n = 100,
+  alpha = 0.05,
+  first_only = TRUE,
+  progress = FALSE
+)
+print(peak)
+```
+This example demonstrates how to estimate the peak time using the `estimate_peak()` function at $95%$ 
+confidence interval and using 100 bootstrap samples. 
+
+
+
 ::::::::::::::::::::::::::::::::::::: challenge 
 
 ## Challenge 1: Can you do it?