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Update <epiparameter> class name in documentation #166

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2 changes: 1 addition & 1 deletion README.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -175,6 +175,6 @@ _cfr_ functionality overlaps with that of some other packages, including
- [_coarseDataTools_](https://cran.r-project.org/package=coarseDataTools) is an R package that allows estimation of relative case fatality risk between covariate groups while accounting for delays due to survival time, when numbers of deaths and recoveries over time are known. _cfr_ uses simpler methods from @nishiura2009 that can be applied when only cases and deaths over time are known, generating estimates based on all data to date, as well as time-varying estimates. _cfr_ can also convert estimates of cases with known outcomes over time into an estimate of under-ascertainment, if a baseline estimate of fatality risk is available from the literature (e.g. from past outbreaks).
- [_EpiNow2_](https://cran.r-project.org/package=EpiNow2) is an R package that can allow estimation of case fatality risk if it is defined as a secondary observation of cases. In particular, it allows for estimation that accounts for the smooth underlying epidemic process, but this requires additional computational effort. A comparison of these methods is planned for a future release.

_cfr_ is in future expected to benefit from the functionality of the forthcoming [_epiparameter_ package](https://epiverse-trace.github.io/epiparameter/), which is also developed by Epiverse-TRACE. _epiparameter_ aims to provide a library of epidemiological parameters to parameterise delay density functions, as well as the convenient `<epidist>` class to store, access, and pass these parameters for delay correction.
_cfr_ is in future expected to benefit from the functionality of the forthcoming [_epiparameter_ package](https://epiverse-trace.github.io/epiparameter/), which is also developed by Epiverse-TRACE. _epiparameter_ aims to provide a library of epidemiological parameters to parameterise delay density functions, as well as the convenient `<epiparameter>` class to store, access, and pass these parameters for delay correction.

## References
2 changes: 1 addition & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -213,7 +213,7 @@ forthcoming [*epiparameter*
package](https://epiverse-trace.github.io/epiparameter/), which is also
developed by Epiverse-TRACE. *epiparameter* aims to provide a library of
epidemiological parameters to parameterise delay density functions, as
well as the convenient `<epidist>` class to store, access, and pass
well as the convenient `<epiparameter>` class to store, access, and pass
these parameters for delay correction.

## References
Expand Down
6 changes: 3 additions & 3 deletions vignettes/delay_distributions.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -157,15 +157,15 @@ Further, _cfr_ functions tally estimated death counts (calculated by convolving
While users can pass functions from _stats_, and can manage distribution parameters using specialised packages and classes, it may be convenient to be able to access parameters reported in the epidemiological literature from a curated library.

The forthcoming [_epiparameter_ package](https://epiverse-trace.github.io/epiparameter/) aims to be such a library of epidemiological delay distributions.
The dedicated `<epidist>` class is expected to have similar functionality to other distribution classes, allowing easy definition of density functions that can be passed to _cfr_.
The dedicated `<epiparameter>` class is expected to have similar functionality to other distribution classes, allowing easy definition of density functions that can be passed to _cfr_.

The pseudo-code below shows how this might work.

```r
# NOTE: this is pseudo-code
EPIDIST_OBJECT <- ACCESS_DISTRIBUTION(disease, study)
EPIPARAMETER_OBJECT <- ACCESS_DISTRIBUTION(disease, study)

cfr_*(data = data, delay_density = function(x) density(<EPIDIST_OBJECT>, x))
cfr_*(data = data, delay_density = function(x) density(<EPIPARAMETER_OBJECT>, x))
```

## References
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