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Merged
merged 13 commits into from
Oct 3, 2023
Merged

workflow/options vignettes #458

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19dda5a
new vignettes
sbfnk Sep 18, 2023
4a21e52
precompile workflow
sbfnk Sep 26, 2023
afb202c
set up for workflow
sbfnk Sep 27, 2023
4005a05
compiled vignettes
sbfnk Sep 27, 2023
a4189ad
add news item
sbfnk Sep 27, 2023
a3674ab
consistent italicisation of EpiNow2
sbfnk Sep 29, 2023
05d8511
consistent () for functions
sbfnk Sep 29, 2023
876eb36
split out epinow() vignette
sbfnk Sep 29, 2023
6c9d255
recompile
sbfnk Sep 29, 2023
da970f5
update pkdown menu
sbfnk Sep 29, 2023
0d796d7
update news
sbfnk Oct 3, 2023
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recompile
sbfnk Oct 3, 2023
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Merge branch 'main' into new-vignettes
sbfnk Oct 3, 2023
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set up for workflow
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@sbfnk
sbfnk committed Sep 27, 2023
commit afb202c6bc2b5766733b1d41067346344f38ab1d
2 changes: 1 addition & 1 deletion vignettes/estimate_infections_options.Rmd.orig
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Expand Up @@ -35,7 +35,7 @@ library("EpiNow2")
library("rstan")
```

We then set the number of cores to use. We will want to run 4 MCMC chains in parallel so we set this to 4. If we had fewer than 4 available or wanted to run fewer than 4 chains (at the expense of some robustness), or had fewer than 4 computing cores available we could set it to that. To find out the number of cores available one can use the [detectCores](https://rdrr.io/r/parallel/detectCores.html) function from the `parallel` package.
In this examples we set the number of cores to use to 4 but the optimal value here will depend on the computing resources available.

```{r}
options(mc.cores = 4)
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14 changes: 14 additions & 0 deletions vignettes/estimate_infections_workflow.Rmd.orig
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Expand Up @@ -41,6 +41,20 @@ A thorough understanding of the data that is used for EpiNow2 and its limitation
This includes but is not limited to biases in the population groups that are represented (EpiNow2 assumes a closed population with all infections being caused by other infections in the same population), reporting artefacts and delays, and completeness of reporting.
Some of these can be mitigated using the routines available in EpiNow2 as described below, but others will cause biases in the results and need to be carefully considered when interpreting the results.

# Set up

We first load the _EpiNow2_ package.

```{r packages}
library("EpiNow2")
```

We then set the number of cores to use. We will want to run 4 MCMC chains in parallel so we set this to 4. If we had fewer than 4 available or wanted to run fewer than 4 chains (at the expense of some robustness), or had fewer than 4 computing cores available we could set it to that. To find out the number of cores available one can use the [detectCores](https://rdrr.io/r/parallel/detectCores.html) function from the `parallel` package.

```{r}
options(mc.cores = 4)
```

# Parameters

Once a data set has been identified, a number of relevant parameters need to be considered before using EpiNow2.
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