Man pages for bairt
Bayesian Analysis of Item Response Theory Models

burning.mcmcBurning of MCMC objects
chain.studyConvergence graphs for the simulated values
chain.study.bairtConvergence graphs for the simulated values
chain.study.defaultConvergence graphs for the simulated values
check.plotPlot of the discrimination marginal posterior means against...
check.plot.defaultPlot of the discrimination marginal posterior means against...
check.plot.mcmc.2pnobPlot of the discrimination marginal posterior means against...
check.plot.mcmc.3pnobPlot of the discrimination marginal posterior means against...
continue.mcmcContinue MCMC for the Estimation of the Two-Parameter or...
continue.mcmc.bairtContinue MCMC for the Estimation of the Two-Parameter or...
continue.mcmc.defaultContinue MCMC for the Estimation of the Two-Parameter or...
data.mcmcMCMC object data
diagnostic.mcmcDiagnostic of _mcmc.2pnob_ or _mcmc.3pnob_ object
final.values.mcmcValues of the last iteration for each chain
ircPlot of posterior density of the item response curve
irc.bairtPlot of posterior density of the item response curve
irc.defaultPlot of posterior density of the item response curve
iter.mcmcNumber of Iterations from an MCMC object.
MathTestObserved data for a math test
mcmc.2pnobMCMC Estimation of the Two-Parameter Normal Ogive Model
mcmc.3pnobMCMC Estimation of the Three-Parameter Normal Ogive Model
model.mcmcMCMC object model
object.codaCreating an mcmc.list for coda package
object.coda.bairtCreating an mcmc.list for coda package
object.coda.defaultCreating an mcmc.list for coda package
parameter.plotGraph of marginal posterior densities
parameter.plot.bairtGraph of marginal posterior densities
parameter.plot.defaultGraph of marginal posterior densities
parts.mcmcNumber of splits for MCMC chain
sabirtShiny App for Bayesian Item Response Theory (SABIRT)
select.c.priorSelect the c prior for the Three-Parameter Normal Ogive Model
thinThinning interval
bairt documentation built on Sept. 4, 2017, 1:02 a.m.