quant_es_core

Computes posterior theta, credible intervals and percentiles for each
variant given a binary evidence matrix.

Implements the Quantification Evidence Standard algorithm for computing
Bayesian evidence sufficiency from binary evidence matrices. It provides
posterior estimates, credible intervals, percentiles, and optional visual
summaries. The method is universal, reproducible, and independent of
any specific clinical or rule based framework. For details see The Quantitative Omics Epidemiology Group et al. (2025) <doi:10.64898/2025.12.02.25341503>.

Dylan Lawless

quantbayes

Bayesian Quantification of Evidence Sufficiency

quant_es_core function

<dl><dt>x</dt>
<dd>matrix of 0 and 1, rows are variants and columns are evidence rules.</dd>
<dt>a</dt>
<dd>prior alpha parameter.</dd>
<dt>b</dt>
<dd>prior beta parameter.</dd>
<dt>ci_level</dt>
<dd>credible interval width.</dd></dl>

Arguments

QuantBayES Universal Bayesian Evidence Sufficiency Scoring — quant_es_core

<dl>

<dt>x</dt>
<dd>matrix of 0 and 1, rows are variants and columns are evidence rules.</dd>


<dt>a</dt>
<dd>prior alpha parameter.</dd>


<dt>b</dt>
<dd>prior beta parameter.</dd>


<dt>ci_level</dt>
<dd>credible interval width.</dd>

</dl>

quant_es_core: QuantBayES Universal Bayesian Evidence Sufficiency Scoring

Description

Usage

Value

Arguments