ggChains {CNPBayes} | R Documentation |
The ggChains
method provides a convenient wrapper for plotting the chains of all parameters in the various mixture model implementations. In addition to the estimated number of independent MCMC draws (effective sample size) and Gelman-Rubin convergence diagnostics implemented in gibbs
, visualization of the chains is helpful for assessing convergence.
ggplot-style functions for diagnosing convergence
ggChains(model) ggMixture(model, bins) ggSingleBatch(model, bins) ggMultiBatch(model, bins) ggSingleBatchChains(model) ## S4 method for signature 'MultiBatchCopyNumber' ggMixture(model, bins) ## S4 method for signature 'MultiBatchCopyNumberPooled' ggMixture(model, bins) ## S4 method for signature 'SingleBatchModel' ggMixture(model, bins) ## S4 method for signature 'MultiBatchModel' ggMixture(model, bins) ## S4 method for signature 'MultiBatchPooled' ggMixture(model, bins) ## S4 method for signature 'SingleBatchCopyNumber' ggMixture(model, bins) ## S4 method for signature 'MultiBatchModel' ggChains(model) ## S4 method for signature 'MultiBatchPooled' ggChains(model) ## S4 method for signature 'SingleBatchPooled' ggChains(model) ## S4 method for signature 'SingleBatchModel' ggChains(model)
model |
A SB, MB, SBP, or MBP model |
bins |
a length-one numeric vector indicating the number of bins – passed to |
The ggMixture
method overlays the posterior approximation of the Gaussian mixture on the empirical data.
A gg
object
a ggplot
object
a list of ggplot
objects. Chains are grouped by the length of
the parameter vector. For example, in the single-batch model, the means
(theta) and variances (sigma2) are component-specific (length k, where k is
number of components) and are plotted together in a single ggplot
object.
sb <- SingleBatchModelExample iter(sb, force=TRUE) <- 1000 burnin(sb) <- 100 sb <- posteriorSimulation(sb) fig.chains <- ggChains(sb) ## component-specific chains fig.chains[["comp"]] ## single-parameter chains and log-likelihood fig.chains[["single"]] ## plot the mixture fig.mix <- ggMixture(sb) sb <- SingleBatchModelExample plist.sb <- ggChains(sb) ## Not run: ## chains for parameter vectors of length k plist.sb[["comp"]] ## chains for parameters vectors of length 1 plist.sb[["single"]] ## End(Not run) mb <- MultiBatchModelExample plist.mb <- ggChains(mb) ## Not run: ## chains for parameters that are batch- and component-specific plist.mb[["batch"]] ## chains for parameters vectors of length k plist.mb[["comp"]] ## chains for parameter vectors of length 1 plist.mb[["single"]] ## End(Not run)