MgsaMcmcResults-class


Instances of this class are used to hold the additional information
that was provided by running (possibly multiple times) an MCMC algorithm.


Model-based Gene Set Analysis (MGSA) is a Bayesian
modeling approach for gene set enrichment. The package mgsa
implements MGSA and tools to use MGSA together with the Gene
Ontology.

Sebastian Bauer

mgsa

Model-based gene set analysis

MgsaMcmcResults-class function

 <dl>
<dt><code>nsamples</code></dt><dd>how many samples collected per MCMC run</dd> <dt><code>steps</code></dt><dd>how many steps per MCMC run</dd> <dt><code>restarts</code></dt><dd>how many MCMC runs</dd> <dt><code>alphaMcmcPost</code></dt><dd>posterior estimates for each MCMC run of the parameter alpha</dd> <dt><code>betaMcmcPost</code></dt><dd>posterior estimates for each MCMC run of the parameter beta</dd> <dt><code>pMcmcPost</code></dt><dd>posterior estimates for each MCMC run of the parameter p</dd> <dt><code>setsMcmcPost</code></dt><dd>posterior estimates for each MCMC run of the sets marginal posterior probabilities The columns of the matrices <code>alphaMcmcPost</code>, <code>betaMcmcPost</code>, <code>pMcmcPost</code> and setsMcmcPost stores the posterior estimates for each individual MCMC run.
The row order matches the one of the slot <code>alphaPost</code>, <code>betaPost</code>, <code>pPots</code>, and <code>setsResults</code> respectively. Accessor methods exist for each slot.</dd> </dl>

Slots

Instances of this class are used to hold the additional information
that was provided by running (possibly multiple times) an MCMC algorithm.

MgsaMcmcResults-class: Instances of this class are used to hold the additional information that was provided by running (possibly multiple times) an MCMC algorithm.

Description

Arguments

Slots

See Also