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Density Plot of spifa Posterior Samples

Source: R/plot-spifa.R
plot_density.Rd

Draws posterior density curves directly from a fitted spifa model, in one of two formats: overlaid (facet = FALSE, the default; stacked, slightly-overlapping ridgeline plot via geom_density_ridges – the more insightful default for comparing many parameters' shapes and locations at a glance) or faceted (facet = TRUE; one panel per parameter). Shows the density shape only – for credible intervals and point estimates, see plot_interval.

Usage

plot_density(
  x,
  select,
  facet = FALSE,
  burnin = 0,
  thin = 1,
  nshow = 10,
  ncol = 1,
  facet_scales = "free",
  scale = 1.2,
  ...
)

Arguments

x

A fitted spifa model.

select

Parameters to plot, as in plot_trace.

facet

Logical; if TRUE, draw one panel per parameter; if FALSE (default), overlay every parameter as a ridgeline plot. See Description.

burnin

Number of initial iterations to discard.

thin

Thinning interval applied after burnin.

nshow

As in plot_trace.

ncol

Number of columns in the facet grid (facet = TRUE only); defaults to a single column.

facet_scales

The scales argument of facet_wrap (facet = TRUE only): one of "free" (default; each panel gets its own x/y-axis), "free_y" (one shared x-axis, line shown only on the bottom panel of each column, matching plot_trace's facet – useful for comparing parameters on a similar scale), "free_x", or "fixed". Parameters with very different value ranges can render compressed/hard to read with a shared x-axis.

scale

Amount of vertical overlap between ridges (facet = FALSE only), passed to geom_density_ridges. Defaults to 1.2.

...

Currently unused.

Value

A ggplot object.

Author

Erick A. Chacón-Montalván

Examples

# \donttest{
data(ipixuna)
samples <- spifa(items ~ 1, data = ipixuna, nfactors = 3, ngp = 0, niter = 1000)

plot_density(samples, select = "c", facet = FALSE)
#> Picking joint bandwidth of 0.0509

plot_density(samples, select = "c", facet = TRUE)


# more than nshow (10) parameters: a random subsample is shown
plot_density(samples, select = "A", facet = FALSE, nshow = 6)
#> Picking joint bandwidth of 0.0973

# }