.format_class

This helper function attempts to determine distribution names and uses those
to establish a class name for potential analytical solutions.

internal

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.

Sam Abbott 

primarycensored

Primary Event Censored Distributions

Sam Abbott

Sam Brand

Adam Howes

James Mba Azam

Carl Pearson

Sebastian Funk

Kelly Charniga

.format_class function

<dl><dt>pdist</dt>
<dd>Distribution function (CDF). The package can identify base R
distributions for potential analytical solutions. For non-base R functions,
users can apply <code>add_name_attribute()</code> to yield properly tagged
functions if they wish to leverage the analytical solutions.</dd>
<dt>dprimary</dt>
<dd>Function to generate the probability density function
(PDF) of primary event times. This function should take a value <code>x</code> and a
<code>pwindow</code> parameter, and return a probability density. It should be
normalized to integrate to 1 over [0, pwindow]. Defaults to a uniform
distribution over [0, pwindow]. Users can provide custom functions or use
helper functions like <code>dexpgrowth</code> for an exponential growth distribution.
See <code>pcd_primary_distributions()</code> for examples. The package can identify
base R distributions for potential analytical solutions. For non-base R
functions, users can apply <code>add_name_attribute()</code> to yield properly tagged
functions if they wish to leverage analytical solutions.</dd></dl>

Arguments

Extract and Combine Distribution Names — .format_class

<dl>

<dt>pdist</dt>
<dd>Distribution function (CDF). The package can identify base R
distributions for potential analytical solutions. For non-base R functions,
users can apply <code>add_name_attribute()</code> to yield properly tagged
functions if they wish to leverage the analytical solutions.</dd>


<dt>dprimary</dt>
<dd>Function to generate the probability density function
(PDF) of primary event times. This function should take a value <code>x</code> and a
<code>pwindow</code> parameter, and return a probability density. It should be
normalized to integrate to 1 over [0, pwindow]. Defaults to a uniform
distribution over [0, pwindow]. Users can provide custom functions or use
helper functions like <code>dexpgrowth</code> for an exponential growth distribution.
See <code>pcd_primary_distributions()</code> for examples. The package can identify
base R distributions for potential analytical solutions. For non-base R
functions, users can apply <code>add_name_attribute()</code> to yield properly tagged
functions if they wish to leverage analytical solutions.</dd>

</dl>

Extract and Combine Distribution Names

.format_class: Extract and Combine Distribution Names

Description

Usage

Value

Arguments