Diagnostic plots for hmclearn

Plots histograms of the posterior estimates. Optionally, displays the 'actual' values given a simulated dataset.

# S3 method for hmclearn
diagplots(
  object,
  burnin = NULL,
  plotfun = 2,
  comparison.theta = NULL,
  cols = NULL,
  ...
)

Arguments

object	an object of class hmclearn, usually a result of a call to mh or hmc
burnin	optional numeric parameter for the number of initial MCMC samples to omit from the summary
plotfun	integer 1 or 2 indicating which plots to display. 1 shows trace plots. 2 shows a histogram
comparison.theta	optional numeric vector of parameter values to compare to the Bayesian estimates
cols	optional integer index indicating which parameters to display
...	currently unused

Value

Returns a customized ggplot object

Examples

# Linear regression example
set.seed(522)
X <- cbind(1, matrix(rnorm(300), ncol=3))
betavals <- c(0.5, -1, 2, -3)
y <- X%*%betavals + rnorm(100, sd=.2)

f <- hmc(N = 1000,
          theta.init = c(rep(0, 4), 1),
          epsilon = 0.01,
          L = 10,
          logPOSTERIOR = linear_posterior,
          glogPOSTERIOR = g_linear_posterior,
          varnames = c(paste0("beta", 0:3), "log_sigma_sq"),
          param=list(y=y, X=X), parallel=FALSE, chains=1)

diagplots(f, burnin=300, comparison.theta=c(betavals, 2*log(.2)))
#> $histogram
#>