Add loading of INLA at start of tutorials

vignettes/covid.Rmd

@@ -24,8 +24,11 @@ The first thing is to load all the packages used in the COVID-19 case study.
 
 The study region is mainland England, which is partitioned into 6789 neighbourhoods at the Middle Layer Super Output Area (MSOA) scale. The shapefile of the study region `shape` is a `SpatialPolygonsDataFrame`, which is used to map the data. It stores the location, shape and attributes of geographic features for the neighbourhoods.load
 
-We first need to retrieve the data from the fdmr example data store and unpack it and we'll use `retrieve_tutorial_data` to do this.
+We first load INLA and then retrieve the data from the fdmr example data store. We'll use `retrieve_tutorial_data` to do this.
 
+```{r}
+library(INLA)
+```
 ```{r}
 fdmr::retrieve_tutorial_data(dataset = "covid")
 ```

vignettes/covid_mcmc.Rmd

@@ -31,7 +31,11 @@ This tutorial requires the [CARBayes package](https://cran.r-project.org/web/pac
 
 The study region is mainland England, which is partitioned into 6789 neighbourhoods at the Middle Layer Super Output Area (MSOA) scale. The infections data are the total reported number of COVID-19 cases in each MSOA from Jan 8, 2022 to March 26, 2022. The shapefile of the study region is a `SpatialPolygonsDataFrame`, which is used to map the data. It stores the location, shape and attributes of geographic features for the neighbourhoods. 
 
-We first need to retrieve the infections data from the fdmr example data store and unpack it and we'll use retrieve_tutorial_data to do this.
+We first load INLA and then retrieve the data from the fdmr example data store. We'll use `retrieve_tutorial_data` to do this.
+
+```{r}
+library(INLA)
+```
 
 ```{r}
 fdmr::retrieve_tutorial_data(dataset = "covid_mcmc")

vignettes/hydro.Rmd

@@ -11,7 +11,11 @@ vignette: >
 
 If you do not have `INLA` or `inlabru` installed [please go to the following installation tutorial before continuing](link%20to%20installation%20tutorial).
 
-First we'll download the data for this tutorial from our [data repository](https://github.com/4DModeller/fdmr_data) using `retrieve_tutorial_data`.
+First we load INLA and then download the data for this tutorial from our [data repository](https://github.com/4DModeller/fdmr_data) using `retrieve_tutorial_data`.
+
+```{r}
+library(INLA)
+```
 
 ```{r error=TRUE,message=FALSE,warning=FALSE}
 fdmr::retrieve_tutorial_data(dataset = "hydro")

vignettes/priors.Rmd

@@ -19,8 +19,10 @@ In this tutorial we'll show an example of exploring the impact of different prio
 
 The study region is Bristol city, which is partitioned into 55 neighbourhoods at the Middle Layer Super Output Area (MSOA) scale. The shapefile of the study region `shape` is a `SpatialPolygonsDataFrame`, which is used to map the data. It stores the location, shape and attributes of geographic features for the neighbourhoods.
 
-We first need to retrieve the data from the fdmr example data store and unpack it and we'll use `retrieve_tutorial_data` to do this.
-
+We first load INLA and then retrieve the data from the fdmr example data store. We'll use `retrieve_tutorial_data` to do this.
+```{r}
+library(INLA)
+```
 ```{r}
 fdmr::retrieve_tutorial_data(dataset = "priors")
 ```