Primary event censored distributions

Summary

Provides functions for working with primary event censored distributions and ‘Stan’ implementations for use in Bayesian modeling. Primary event censored distributions are useful for modeling delayed reporting scenarios in epidemiology and other fields (Charniga et al. (2024) doi:10.48550/arXiv.2405.08841). It also provides support for arbitrary delay distributions, a range of common primary distributions, and allows for truncation and secondary event censoring to be accounted for (Park et al. (2024) doi:10.1101/2024.01.12.24301247). A subset of common distributions also have analytical solutions implemented, allowing for faster computation. In addition, it provides multiple methods for fitting primary event censored distributions to data via optional dependencies.

Installation

Installing the package

You can install the latest released version from CRAN using the standard install.packages function:

install.packages("primarycensored")

Alternatively, you can install the latest release from our r-universe repository:

install.packages("primarycensored", repos = "https://epinowcast.r-universe.dev")

To install the development version from GitHub (warning! this version may contain breaking changes and/or bugs), use the pak package:

pak::pak("epinowcast/primarycensored")

Similarly, you can install historical versions by specifying the release tag (e.g., v0.2.0):

pak::pak("epinowcast/[email protected]")

Note: You can also use the above approach to install a specific commit if needed, for example, if you want to try out a specific unreleased feature, but not the absolute latest developmental version.

Installing CmdStan (optional for Stan functionality)

If you wish to use the Stan functions, you will need to install CmdStan, which also entails having a suitable C++ toolchain setup. We recommend using the cmdstanr package. The Stan team provides instructions in the Getting started with cmdstanr vignette, with other details and support at the package site along with some key instructions available in the Stan resources package vignette, but the brief version is:

# if you not yet installed `primarycensored`, or you installed it without
# `Suggests` dependencies
install.packages(
  "cmdstanr",
  repos = c("https://stan-dev.r-universe.dev", getOption("repos"))
)
# once `cmdstanr` is installed:
cmdstanr::install_cmdstan()

Note: You can speed up CmdStan installation using the cores argument. If you are installing a particular version of epinowcast, you may also need to install a past version of CmdStan, which you can do with the version argument.

Resources

We provide a range of other documentation, case studies, and community spaces to ask (and answer!) questions:

Package Website

The primarycensored website includes a function reference, model outline, and case studies using the package. The site mainly concerns the release version, but you can also find documentation for the latest development version.

Vignettes

We have created package vignettes to help you get started with primarycensored and to highlight other features with case studies.

Organisation Website

Our organisation website includes links to other resources, guest posts, and seminar schedule for both upcoming and past recordings.

Community Forum

Our community forum has areas for question and answer and considering new methods and tools, among others. If you are generally interested in real-time analysis of infectious disease, you may find this useful even if you do not use primarycensored.

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