minor changes to the vignette

Author: gcorani

vignettes/bayesRecon.Rmd

@@ -171,7 +171,6 @@ A <- recon.matrices$A
 To reconcile using Bottom-Up Important Sampling (BUIS) we
 we use the function `reconc_BUIS`, passing to it
 the $\mathbf{S}$ matrix, the *base forecasts*, the  type  of the base forecasts (`in_type`="samples") and whether the samples are discrete or integer (`distr` = "discrete").
-The  examples shown later perform instead reconciliation of Gaussian base forecasts, in which case  (`in_type`="params").
 
 
 ``` {r reconc}
@@ -183,7 +182,8 @@ recon.res <- bayesRecon::reconc_BUIS(
   seed = 42
 )
 ```
-The function returns samples from the  *reconciled forecast distribution*.
+
+Here we obtain samples from the reconciled forecast distribution.
 ```{r res}
 reconciled_samples <- recon.res$reconciled_samples
 dim(reconciled_samples)
@@ -392,7 +392,7 @@ for (s in infantMortality) {
 }
 ```
 
-Build the $\mathbf{S}$ matrix.
+Now we build the $\mathbf{S}$ matrix.
 
 ```{r infants-s, dpi=300, out.width = '70%', fig.align='center', fig.cap="**Figure 6**: Infants mortality - The aggregating matrix A (red=1, yellow=0).", fig.dim = c(8, 8)}
 # we have 16 bottom time series, and 11 upper time series