Added links to YouTube videos

Author: MarcoRianiUNIPR

README.md

@@ -1,7 +1,7 @@
 # Applied Robust Statistics through the Monitoring Approach: Applications in Regression
 GitHub repo of the forthcoming book "Applied Robust Statistics through the Monitoring Approach: 
 Applications in Regression" Heidelberg: Springer Nature. by 
-Atkinson,A.C., Riani,M., Corbellini,A., Perrotta D., and Todorov,V. (2024), 
+Atkinson,A.C., Riani,M., Corbellini,A., Perrotta D., and Todorov,V. (2025), 
 
 
 **Reproducible Research (run in MATLAB on line or see Jupyter notebook file with attached output)**
@@ -24,19 +24,75 @@ A YouTube video summarizing the contents of the book can be found at the link be
 Additional YouTube videos can be found inside the individual chapters.
 
 
-1. Introduction and the Grand Plan  [[open dir](cap1/README.md)]  
-2. Introduction to M-Estimation for Univariate Samples[[open dir](cap2/README.md)]  
-3. Robust Estimators in Multiple Regression  [[open dir](cap3/README.md)]  
-4. The Monitoring Approach in Multiple Regression [[open dir](cap4/README.md)]  
+1. **Introduction and the Grand Plan**  [[open dir](cap1/README.md)]  
+>>> <a href="https://youtu.be/jSLNEa5VTN4?si=bPYYXl1pqrdHu2Jt"> Introduction and the Grand Plan <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+<br>
+
+2. **Introduction to M-Estimation for Univariate Samples**[[open dir](cap2/README.md)]  
+>>> <a href="https://youtu.be/4wP0rbELIjE?si=XETW6XZM5HlIPu4o"> Introduction to M-Estimation for Univariate Samples PART I <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>>  <a href="https://youtu.be/g_mvTRs4LjY?si=4s4folepyrN5nJ1v"> Introduction to M-Estimation for Univariate Samples PART II <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+<br>
+
+3. **Robust Estimators in Multiple Regression**  [[open dir](cap3/README.md)]  
+>>> <a href="https://youtu.be/X_P8bQABQrw?si=kLWM016_IBek1HTK"> Analysis of the AR regression data <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
+4. **The Monitoring Approach in Multiple Regression** [[open dir](cap4/README.md)]  
+
+>>> <a href="https://youtu.be/MMPVy7G41T8?si=nsHGPxpgcuD0twW5"> Outlier detection with the forward search (Sections 4.1-4.5 and 4.9.5) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="analysis of the Hawkins data (Section 4.9.4)"> Analysis of the Hawkins data (Section 4.9.4) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/z-cCFCYiwpU?si=vPw50MDypy52keSW"> Analysis of the bank data (Section 4.10) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
 5.  Practical Comparison of the Different Estimators [[open dir](cap5/README.md)]  
+
 6.  Transformations  [[open dir](cap6/README.md)]  
-7.  Non-parametric Regression  [[open dir](cap7/README.md)]  
+>>> <a href="https://youtu.be/KOPYSeNgKPM?si=Ealxz6k738mmp0Oy"> Transformation of the response <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
+7.  Non-parametric Regression  [[open dir](cap7/README.md)] 
+
+>>> <a href="https://youtu.be/Q7D3HioOxHQ?si=iC5gNyOYEvtOlkbp"> Non parametric transformations (part I) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/bvOWwGmxRko?si=m0FtPkrlU4ctTizY"> Non parametric transformations (part II) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
+
 8.   Extensions of the Multiple Regression Model   [[open dir](cap8/README.md)]  
+>>> <a href="https://youtu.be/Op_yXrdhiDg?si=RVkitOUWg5EAGRuu"> Robust Bayesian regression (Sections 8.1- 8.3) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/QLnSTc5g19A?si=tP0L3BwOLrvUypxX"> Heteroskedastic regression (Section 8.4) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
+
 9.    Model selection    [[open dir](cap9/README.md)]
+
+>>> <a href="https://youtu.be/xFNGnEgDam4?si=l5WOOcGj6L4Hy9u-"> Variable Selection Mallow's Cp and the generalized candlestick plot (Section 9.3) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
 10.   Some Robust Data Analyses    [[open dir](cap10/README.md)]
 
+>>> <a href="https://youtu.be/wj3k2-Ca-f4?si=eX5OyqddUGxTpkdP"> Income data 1: regression analysis (Section 10.2) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/6EF3Nk1yzTE?si=e3Trx-w9RZ4dN9X5"> Income data 2: regression analysis (Section 10.3) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/0mVbMqh99_4?si=EC8tpKd4cpWEfE9i"> Analysis of the customer loyalty data (Section 10.4) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/YT8exrmVpdg?si=VaVjkWBNSIK0EaNN"> Analysis of the modified customer loyalty data (Section 10.5) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/1RF3wj1Ml8Y?si=0WEMm-4qD4eNSscH"> Analysis of the NCI60 Cancer Cell Panel Data (Part II, Section 10.6) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+
+
 Appendix.   Solution to the Exercises [[open dir](solutionsEX/README.md)]
 
+>>> <a href="https://youtu.be/2TFwB-Rf3G8?si=iRNL0MurPz5leB_Z"> Analysis of the heart rate data (Exercise 10.1) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
+>>> <a href="https://youtu.be/pYdO688nvOk?si=LwAu9BKInyHxgcKQ"> Analysis of the auto mpg data (Exercise 10.4) <img src="https://upload.wikimedia.org/wikipedia/commons/b/b8/YouTube_Logo_2017.svg" alt="YouTube Logo" width="100"></a>
+
 # Code by dataset
 In the book there are datasets which are used in different Chapters.
 Here you can find the link to the folder which contains the 
@@ -61,7 +117,7 @@ $$
     isbn = {XXX-XXXXXX},   
     publisher = {Heidelberg: Springer Nature},  
     title = {Applied Robust Statistics through the Monitoring Approach, Applications in Regression},  
-    year = {2024}  
+    year = {2025}  
     }