README.Rmd

---
output: github_document
---

```{r setup, echo = FALSE, message=FALSE, results='hide'}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.align = "center",
  fig.path = "man/figures/README-",
  echo = TRUE,
  fig.width = 8,
  fig.height = 6
)

```

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# Scope

*i2extras* adds additional functionality to the
[incidence2](https://github.com/reconverse/incidence2) package.

# What does it do?

The main features of the package include:

- `fit_curve()` and `growth_rate()`: fit a trend (poisson / negative
  binomial) to an `incidence2` object and calculate the associated growth
  rate.

- `add_rolling_average()`: add a rolling average to an `incidence2` object.

- `bootstrap()`: generates a bootstrapped `incidence2` object by re-sampling,
  with replacement, the original dates of events.

- `find_peak()`: locates the peak time of the epicurve.

- `estimate_peak()`: uses bootstrap to estimate the peak time (and related
  confidence interval) of a partially observed outbreak.


## Installing the package

You can install the released version of {i2extras} from [CRAN](https://cran.r-project.org/) with:

```{r, eval=FALSE}
install.packages("i2extras")
```

::: {.pkgdown-devel}
The development version of {i2extras} can be installed from GitHub with:
```{r, eval=FALSE}
remotes::install_github("reconverse/i2extras", build_vignettes = TRUE)
```
:::

# Resources

## Vignettes

An overview of *i2extras* is provided in the included vignettes:

* `vignette("peak_estimation", package = "i2extras")`

* `vignette("fitting_epicurves", package = "i2extras")`


## Getting help online

Bug reports and feature requests should be posted on *github* using the 
[*issue* system](https://github.com/reconverse/i2extras/issues). All other 
questions should be posted on the **RECON** slack channel see
<https://www.repidemicsconsortium.org/forum/> for details on how to join.