.check_truncation_bounds_df

Internal function to validate that L (lower truncation) is less than D
(upper truncation) for all rows in a data frame.

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_df function

<dl><dt>data</dt>
<dd>Data frame containing the L and D columns</dd>
<dt>L_col</dt>
<dd>Name of the column containing L values</dd>
<dt>D_col</dt>
<dd>Name of the column containing D values</dd></dl>

Arguments

Validate truncation bounds in a data frame — .check_truncation_bounds_df

<dl>

<dt>data</dt>
<dd>Data frame containing the L and D columns</dd>


<dt>L_col</dt>
<dd>Name of the column containing L values</dd>


<dt>D_col</dt>
<dd>Name of the column containing D values</dd>

</dl>

Validate truncation bounds in a data frame

.check_truncation_bounds_df: Validate truncation bounds in a data frame

Description

Usage

Value

Arguments