MCMC-combos: Combination plots

In bayesplot: Plotting for Bayesian Models

Combination plots

Description

Combination plots

Usage

mcmc_combo(x, combo = c("dens", "trace"), ..., widths = NULL, gg_theme = NULL)

Arguments

x	An object containing MCMC draws: A 3-D array, matrix, list of matrices, or data frame. The MCMC-overview page provides details on how to specify each these. A draws object from the posterior package (e.g., draws_array, draws_rvars, etc.). An object with an as.array() method that returns the same kind of 3-D array described on the MCMC-overview page.
combo	A character vector with at least two elements. Each element of combo corresponds to a column in the resulting graphic and should be the name of one of the available MCMC functions (omitting the mcmc_ prefix).
...	Arguments passed to the plotting functions named in combo.
widths	A numeric vector the same length as combo specifying relative column widths. For example, if the plot has two columns, then widths = c(2, 1) will allocate more space for the first column by a factor of 2 (as would widths = c(.3, .15), etc.). The default, NULL, allocates the same horizontal space for each column.
gg_theme	Unlike most of the other bayesplot functions, mcmc_combo returns a gtable object rather than a ggplot object, and so theme objects can't be added directly to the returned plot object. The gg_theme argument helps get around this problem by accepting a ggplot2 theme object that is added to each of the plots before combining them into the gtable object that is returned. This can be a theme object created by a call to ggplot2::theme() or one of the bayesplot convenience functions, e.g. legend_none() (see the Examples section, below).

Value

A gtable object (the result of calling gridExtra::arrangeGrob()) with length(combo) columns and a row for each parameter.

See Also

Other MCMC: MCMC-diagnostics, MCMC-distributions, MCMC-intervals, MCMC-nuts, MCMC-overview, MCMC-parcoord, MCMC-recover, MCMC-scatterplots, MCMC-traces

Examples

# some parameter draws to use for demonstration
x <- example_mcmc_draws()
dim(x)
dimnames(x)

mcmc_combo(x, pars = c("alpha", "sigma"))
mcmc_combo(x, pars = c("alpha", "sigma"), widths = c(1, 2))


# change second plot, show log(sigma) instead of sigma,
# and remove the legends
color_scheme_set("mix-blue-red")
mcmc_combo(
 x,
 combo = c("dens_overlay", "trace"),
 pars = c("alpha", "sigma"),
 transformations = list(sigma = "log"),
 gg_theme = legend_none()
)

# same thing but this time also change the entire ggplot theme
mcmc_combo(
 x,
 combo = c("dens_overlay", "trace"),
 pars = c("alpha", "sigma"),
 transformations = list(sigma = "log"),
 gg_theme = ggplot2::theme_gray() + legend_none()
)

bayesplot documentation built on May 29, 2024, 2:27 a.m.