The function plots a set of densities (per chain and coefficient) from the MCMC sample of an object of class "JointAI".

densplot(object, ...)

# S3 method for JointAI
densplot(object, start = NULL, end = NULL, thin = NULL,
  subset = c(analysis_main = TRUE), outcome = NULL,
  exclude_chains = NULL, vlines = NULL, nrow = NULL, ncol = NULL,
  joined = FALSE, use_ggplot = FALSE, warn = TRUE, mess = TRUE, ...)

Arguments

object

object inheriting from class 'JointAI'

...

additional parameters passed to plot()

start

the first iteration of interest (see window.mcmc)

end

the last iteration of interest (see window.mcmc)

thin

thinning interval (integer; see window.mcmc). For example, thin = 1 (default) will keep the MCMC samples from all iterations; thin = 5 would only keep every 5th iteration.

subset

subset of parameters/variables/nodes (columns in the MCMC sample). Follows the same principle as the argument monitor_params in *_imp.

outcome

optional; vector identifying a subset of sub-models included in the output, either by specifying their indices (using the order used in the list of model formulas), or their names (LHS of the respective model formula as character string)

exclude_chains

optional vector of the index numbers of chains that should be excluded

vlines

list, where each element is a named list of parameters that can be passed to graphics::abline() to create vertical lines. Each of the list elements needs to contain at least v = <x location>, where <x location> is a vector of the same length as the number of plots (see examples).

nrow

optional; number of rows in the plot layout; automatically chosen if unspecified

ncol

optional; number of columns in the plot layout; automatically chosen if unspecified

joined

logical; should the chains be combined before plotting?

use_ggplot

logical; Should ggplot be used instead of the base graphics?

warn

logical; should warnings be given? Default is TRUE.

mess

logical; should messages be given? Default is TRUE.

See also

The vignette Parameter Selection contains some examples how to specify the argument subset.

Examples


if (FALSE) {
# fit a JointAI object:
mod <- lm_imp(y ~ C1 + C2 + M1, data = wideDF, n.iter = 100)

# Example 1: basic densityplot
densplot(mod)
densplot(mod, exclude_chains = 2)


# Example 2: use vlines to mark zero
densplot(mod, col = c("darkred", "darkblue", "darkgreen"),
         vlines = list(list(v = rep(0, nrow(summary(mod)$res$y$regcoef)),
                            col = grey(0.8))))


# Example 3: use vlines to visualize posterior mean and 2.5%/97.5% quantiles
res <- rbind(summary(mod)$res$y$regcoef[, c('Mean', '2.5%', '97.5%')],
             summary(mod)$res$y$sigma[, c('Mean', '2.5%', '97.5%'),
             drop = FALSE]
             )
densplot(mod, vlines = list(list(v = res[, "Mean"], lty = 1, lwd = 2),
                            list(v = res[, "2.5%"], lty = 2),
                            list(v = res[, "97.5%"], lty = 2)))


# Example 4: ggplot version
densplot(mod, use_ggplot = TRUE)


# Example 5: change how the ggplot version looks
library(ggplot2)

densplot(mod, use_ggplot = TRUE) +
  xlab("value") +
  theme(legend.position = 'bottom') +
  scale_color_brewer(palette = 'Dark2', name = 'chain')
}