Minor changes to references for the vignettes

vignettes/mixed_reconciliation.Rmd

@@ -69,7 +69,7 @@ rec_fc <- list(
 
 # Gaussian reconciliation
 
-We perform Gaussian reconciliation (`Gauss`) first. 
+We perform Gaussian reconciliation (`Gauss`, [@corani2021probabilistic]) first. 
 It assumes  all forecasts to be Gaussian, even though the bottom base forecasts are not Gaussian. 
 
 We assume the upper base forecasts to be a multivariate Gaussian and we estimate their  covariance matrix from the in-sample residuals. We assume also the bottom base forecasts to be independent Gaussian.

vignettes/references.bib

@@ -130,7 +130,8 @@ @InProceedings{corani2021probabilistic
   booktitle="Machine Learning and Knowledge Discovery in Databases",
   year="2021",
   publisher="Springer International Publishing",
-  pages="211--226"
+  pages="211--226",
+  doi="10.1007/978-3-030-67664-3_13"
 }
 
 @article{zambon2022efficient,
@@ -191,8 +192,7 @@ @inproceedings{zambon2024mixed
   title={Probabilistic reconciliation of mixed-type hierarchical time series},
   author={Zambon, Lorenzo and Azzimonti, Dario and Rubattu, Nicolò and Corani, Giorgio},
   booktitle={The 40th Conference on Uncertainty in Artificial Intelligence},
-  year={2024},
-  url={https://openreview.net/forum?id=KmbmBlrQkr}
+  year={2024}
 }
 
 @article{MAKRIDAKIS20221325,
@@ -203,7 +203,8 @@ @article{MAKRIDAKIS20221325
     pages = {1325-1336},
     year = {2022},
     author = {Spyros Makridakis and Evangelos Spiliotis and Vassilios Assimakopoulos},
-    keywords = {Forecasting competitions, M competitions, Accuracy, Uncertainty, Time series, Retail sales forecasting}
+    keywords = {Forecasting competitions, M competitions, Accuracy, Uncertainty, Time series, Retail sales forecasting},
+    doi = {10.1016/j.ijforecast.2021.07.007}
 }
 
 @article{svetunkov2023iets,
@@ -213,7 +214,8 @@ @article{svetunkov2023iets
   volume={265},
   pages={109013},
   year={2023},
-  publisher={Elsevier}
+  publisher={Elsevier},
+  doi={10.1016/j.ijpe.2023.109013}
 }