From eb2b909dd4e2fd6ccb320730d35719de7a53ea6b Mon Sep 17 00:00:00 2001
From: Delaigue Olivier <olivier.delaigue@irstea.fr>
Date: Fri, 26 Mar 2021 14:43:37 +0100
Subject: [PATCH] docs(vignette): review style in param_optim and
 param_sets_GR4J

---
 vignettes/V02.1_param_optim.Rmd   | 1 +
 vignettes/V03_param_sets_GR4J.Rmd | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/vignettes/V02.1_param_optim.Rmd b/vignettes/V02.1_param_optim.Rmd
index ac2e701e..bcd3f3e8 100644
--- a/vignettes/V02.1_param_optim.Rmd
+++ b/vignettes/V02.1_param_optim.Rmd
@@ -205,6 +205,7 @@ resGLOB
 
 Multiobjective optimization is used to explore possible trade-offs between different performances criteria.
 Here we use the following R implementation of an efficient strategy:
+
 * [caRamel: Automatic Calibration by Evolutionary Multi Objective Algorithm](https://cran.r-project.org/package=caRamel)
 
 Motivated by using the rainfall-runoff model for low flow simulation, we explore the trade-offs between the KGE values obtained without any data transformation and with the inverse transformation.
diff --git a/vignettes/V03_param_sets_GR4J.Rmd b/vignettes/V03_param_sets_GR4J.Rmd
index 36eb29c5..5409731a 100644
--- a/vignettes/V03_param_sets_GR4J.Rmd
+++ b/vignettes/V03_param_sets_GR4J.Rmd
@@ -141,7 +141,7 @@ Now we can compute the Nash-Sutcliffe Efficiency criterion on the validation per
 
 
 
-# Calibration of the GR4J model with the built-in `Calibration_Michel()` function
+# Calibration of the GR4J model with the built-in Calibration_Michel function
 
 As seen above, the Michel's calibration algorithm is based on a local search procedure.
 
-- 
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