MgsaMcmcResults

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 function

 <ul>
<li>stepshow many steps per MCMC run </li>
<li>restartshow many MCMC runs </li>
<li>alphaMcmcPostposterior estimates for each MCMC
  run of the parameter alpha </li>
<li>betaMcmcPostposterior estimates for each MCMC run
  of the parameter beta </li>
<li>pMcmcPostposterior estimates for each MCMC run of
  the parameter p </li>
<li>setsMcmcPostposterior 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.
</li>
</ul>

MgsaMcmcResults: 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