Fix some minor problems

index.qmd

@@ -938,6 +938,7 @@ plot(rowSums(X * w),
 ::: {.column width="48%"}
 
 Each day, $t = 1, 2, ... T$
+
 - The **forecaster** receives predictions $\widehat{X}_{t,k}$ from $K$ **experts**
 - The **forecaster** assings weights $w_{t,k}$ to each **expert**
 - The **forecaster** calculates her prediction:
@@ -945,8 +946,7 @@ Each day, $t = 1, 2, ... T$
     \widetilde{X}_{t} = \sum_{k=1}^K w_{t,k} \widehat{X}_{t,k}.
     \label{eq_forecast_def}
 \end{equation}
-- The realization for $t$ is observedilities
-  - Vertical aggregation
+- The realization for $t$ is observed
 
 :::
 
@@ -1023,7 +1023,7 @@ Strictly proper for *median* predictions
 
 :::: {.columns}
 
-::: {.column width="58%"}
+::: {.column width="48%"}
 
 ### Popular Aggregation Algorithms
 
@@ -1046,15 +1046,13 @@ w_{t,k}^{\text{Naive}} = \frac{1}{K}\label{eq:naive_combination}
   \end{aligned}\label{eq:exp_combination}
 \end{equation}
 
-Du kannst dann auch easy darauf verweisen: \ref{eq:exp_combination}.
-
 :::
 
 ::: {.column width="4%"}
 
 :::
 
-::: {.column width="38%"}
+::: {.column width="48%"}
 
 ### Optimality