update link to day 3 and 4 tutorials in the index

_quarto.yml

@@ -56,6 +56,7 @@ book:
         - chapters/day1_what-eco-net2.qmd
         - chapters/day1_why-net.qmd
         - chapters/day2_metrics.qmd
+        - chapters/day2_complex-stab.qmd
         - chapters/day3_sbm.qmd
         - chapters/day4_multilevel.qmd
         - chapters/day5_collection.qmd

chapters/TutorialBM.qmd

@@ -1,8 +1,4 @@
 ---
-title: "Tutorial on Stochastic Block Models"
-subtitle: "April 2024"
-author: "Econet group"
-date: "04/24/2024"
 output:
   rmarkdown::html_vignette:
   toc: true
@@ -25,8 +21,10 @@ comment = "#>"
 
 ```
 
+
+# Tutorial on Stochastic Block Models {.unnumbered}
 
-# 0.Requirements
+# 0.Requirements  {.unnumbered}
 
 This tutorial illustrates the use of block models for the analysis of (ecological) network.
 Is is mainly based on the vignette of the package `sbm`.
@@ -56,7 +54,7 @@ library(RColorBrewer)
 library(knitr)
 ```
 
-# 1. Simulating network data
+# 1. Simulating network data  {.unnumbered}
 
 Let us first simulate networks using the `sbm` package.
 
@@ -107,7 +105,7 @@ sbm::plotMyMatrix(myMat,dimLabels = list(row = "species", col = "species"),plotO
 
 **Exercice** Modify the structure by choosing other parameters and compute the statistics that you learned the previous days. Use `igraph` to plot your new networks. For instance, you may try to simulate a foodweb with 5 trophic levels.
 
-## 1.B. Bipartite networks
+## 1.B. Bipartite networks  {.unnumbered}
 
 **Exercice** Use the function `sampleBipartiteSBM` to simulate a weighted (counts) bipartite network with the following parameters.
 
@@ -129,7 +127,7 @@ mySampler
 
 
 
-# 2. Analyzing an ecological data set
+# 2. Analyzing an ecological data set  {.unnumbered}
 
 ## 2.A. The data set: antagonistic tree/fungus interaction network
 
@@ -431,7 +429,7 @@ plot(myBipartiteSBM, type = "expected")
 
 
 
-# 3.  The Shiny application
+# 3.  The Shiny application  {.unnumbered}
 
 We (T. Vanrenterghem (INRAE))  are developing a Shiny application to help people use our package. 
 

chapters/TutorialDattilo.qmd

@@ -1,8 +1,4 @@
 ---
-title: "Tutorial on Multipartite block models"
-subtitle: "April 2024"
-author: "Econet group"
-date: "04/24/2024"
 output:
   rmarkdown::html_vignette:
   toc: true
@@ -21,10 +17,9 @@ comment = "#>"
 )
 ```
 
+# Tutorial on Multipartite block models {.unnumbered}
 
-
-
-# 0.Requirements
+# 0.Requirements {.unnumbered}
 
 This tutorial illustrates the use of block models for the analysis of (ecological) multipartite network.
 Is is mainly based on a [vignette](https://grosssbm.github.io/sbm/articles/Multipartite_EcologicalNetwork.html) of the package `sbm` .
@@ -42,7 +37,7 @@ library(sbm)
 library(ggplot2)
 ```
 
-# 1. What if I have more than 2 types of nodes? 
+# 1. What if I have more than 2 types of nodes? {.unnumbered}
 
 The sbm package is able to handle multipartite networks, meaning that they involve more that two types of nodes and intra and inter groups connections. 
 We analyse the data from @Dattilo with the method proposed by  @multipartite.