log_BF

log_BF.default

log_BF.sim_reg_output

Calculate log Bayes factor for similarity the model, <code>gamma=1</code> and baseline model, <code>gamma=0</code>.

Similarity regression,
evaluating the probability of association between sets of ontological terms
and binary response vector. A no-association model is compared with one in which
the log odds of a true response is linked to the semantic similarity
between terms and a latent characteristic ontological profile - 'Phenotype Similarity Regression for Identifying the Genetic Determinants of Rare Diseases', Greene et al 2016 <doi:10.1016/j.ajhg.2016.01.008>.

Daniel Greene

SimReg

Similarity Regression

log_BF function

<dl><dt>x</dt>
<dd><code>list</code> of term sets or <code>sim_reg_output</code> object.</dd>
<dt>...</dt>
<dd>If x is a <code>list</code> term sets, other arguments to pass to <code>sim_reg</code>, otherwise this is not used.</dd></dl>

Arguments

Calculate log Bayes factor for similarity the model, gamma=1 and baseline model, gamma=0. — log_BF

<dl>

<dt>x</dt>
<dd><code>list</code> of term sets or <code>sim_reg_output</code> object.</dd>


<dt>...</dt>
<dd>If x is a <code>list</code> term sets, other arguments to pass to <code>sim_reg</code>, otherwise this is not used.</dd>

</dl>

log_BF: Calculate log Bayes factor for similarity the model, `gamma=1` and baseline model, `gamma=0`.

Description

Usage

Value

Arguments