getExpectedMeasIntervals

This functions uses posterior samples to quantify uncertainty in the
expected measurements from fitted models.

Fit linear models based on periodic splines, moderate model
coefficients using multivariate adaptive shrinkage, then compute properties of
the moderated curves.

Jake Hughey

limorhyde2

Quantify Rhythmicity and Differential Rhythmicity in Genomic
Data

Dora Obodo

Elliot Outland

getExpectedMeasIntervals function

<dl><dt>expectedMeas</dt>
<dd>A <code>data.table</code> of expected measurements for posterior
samples, as returned by <code>getExpectedMeas()</code>.</dd>
<dt>mass</dt>
<dd>Number between 0 and 1 indicating the probability mass for which
to calculate the intervals.</dd>
<dt>method</dt>
<dd>String indicating the type of interval: 'eti' for equal-tailed
using <code><a href="/link/stats%3A%3Aquantile()?package=limorhyde2&version=0.1.1" data-mini-rdoc="limorhyde2::stats::quantile()">stats::quantile()</a></code>, or 'hdi' for highest density using
<code>HDInterval::hdi()</code>.</dd></dl>

Arguments

Compute credible intervals for expected measurements — getExpectedMeasIntervals

<dl>

<dt>expectedMeas</dt>
<dd>A <code>data.table</code> of expected measurements for posterior
samples, as returned by <code>getExpectedMeas()</code>.</dd>


<dt>mass</dt>
<dd>Number between 0 and 1 indicating the probability mass for which
to calculate the intervals.</dd>


<dt>method</dt>
<dd>String indicating the type of interval: 'eti' for equal-tailed
using <code><a href='https://rdrr.io/r/stats/quantile.html'>stats::quantile()</a></code>, or 'hdi' for highest density using
<code>HDInterval::hdi()</code>.</dd>

</dl>

getExpectedMeasIntervals: Compute credible intervals for expected measurements

Description

Usage

Value

Arguments

See Also

Examples