PlotMean: Plot Mean

In bfw: Bayesian Framework for Computational Modeling

Plot Mean

Description

Create a (repeated) mean plot

Usage

PlotMean(
  data,
  monochrome = TRUE,
  plot.colors = c("#495054", "#e3e8ea"),
  font.type = "serif",
  run.repeated = FALSE,
  run.split = FALSE,
  y.split = FALSE,
  ribbon.plot = TRUE,
  y.text = "Score",
  x.text = NULL,
  remove.x = FALSE
)

Arguments

data	MCMC data to plot
monochrome	logical, indicating whether or not to use monochrome colors, else use DistinctColors, Default: TRUE
plot.colors	range of color to use, Default: c("#495054", "#e3e8ea")
font.type	font type used for visualizations, Default: 'serif'
run.repeated	logical, indicating whether or not to use repeated measures plot, Default: FALSE
run.split	logical, indicating whether or not to use split violin plot and compare distribution between groups, Default: FALSE
y.split	logical, indicating whether or not to split within (TRUE) or between groups, Default: FALSE
ribbon.plot	logical, indicating whether or not to use ribbon plot for HDI, Default: TRUE
y.text	label on y axis, Default: 'Score'
x.text	label on x axis, Default: NULL
remove.x	logical, indicating whether or not to show x.axis information, Default: FALSE

See Also

ggproto, ggplot2-ggproto, aes, margin, geom_boxplot, geom_crossbar, geom_path, geom_ribbon, geom_violin, ggplot, scale_manual, scale_x_discrete, theme, layer, labs arrange, rbind.fill zero_range grid.grob, grobName, unit approxfun colorRamp

bfw documentation built on March 18, 2022, 6:19 p.m.