.check_truncation_bounds

Internal function to validate that L (lower truncation) and D (upper
truncation) parameters are valid: L must be non-negative and less than D.

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

.check_truncation_bounds function

<dl><dt>L</dt>
<dd>Lower truncation bound</dd>
<dt>D</dt>
<dd>Upper truncation bound</dd></dl>

Arguments

Validate truncation bounds L and D — .check_truncation_bounds

<dl>

<dt>L</dt>
<dd>Lower truncation bound</dd>


<dt>D</dt>
<dd>Upper truncation bound</dd>

</dl>

Validate truncation bounds L and D

.check_truncation_bounds: Validate truncation bounds L and D

Description

Usage

Value

Arguments