sample_distrib

Sample from a (possibly multivariate) t-distribution. This function can be
used to sample both from a prior or posterior, depending on the value of
parameters provided.

Bayesian toolbox for quantitative proteomics. In particular, this
package provides functions to generate synthetic datasets, execute Bayesian
differential analysis methods, and display results as, described in the
associated article Marie Chion and Arthur Leroy (2023) <arXiv:2307.08975>.

Arthur Leroy

ProteoBayes

Bayesian Statistical Tools for Quantitative Proteomics

Marie Chion

sample_distrib function

<dl><dt>posterior</dt>
<dd>A tibble or data frame, detailing for each <code>Peptide</code>
and each <code>Group</code>, the value of the t-distribution parameters. The
expected format is typically a return from a posterior_mean() function.
Expected columns in the univariate case: <code>mu</code>, <code>lambda</code>,
<code>alpha</code>, <code>beta</code>. Expected columns in the multivariate case:
<code>mu</code>, <code>lambda</code>, <code>Sigma</code>, <code>nu</code>.</dd>
<dt>nb_sample</dt>
<dd>A number, indicating the number of samples generated for
each couple <code>Peptide</code>-<code>Group</code>.</dd></dl>

Arguments

Sample from a t-distribution — sample_distrib

<dl>

<dt>posterior</dt>
<dd>A tibble or data frame, detailing for each <code>Peptide</code>
and each <code>Group</code>, the value of the t-distribution parameters. The
expected format is typically a return from a posterior_mean() function.
Expected columns in the univariate case: <code>mu</code>, <code>lambda</code>,
<code>alpha</code>, <code>beta</code>. Expected columns in the multivariate case:
<code>mu</code>, <code>lambda</code>, <code>Sigma</code>, <code>nu</code>.</dd>


<dt>nb_sample</dt>
<dd>A number, indicating the number of samples generated for
each couple <code>Peptide</code>-<code>Group</code>.</dd>

</dl>

sample_distrib: Sample from a t-distribution

Description

Usage

Value

Arguments

Examples