plot.pppds: Plots histograms using the compact axis notation from the...

In carlislerainey/separation: Using informative priors to deal with separation in logistic regression models

Description

plot.pppds() plots histograms using the compact axis notation from the compactr package.

Usage

## S3 method for class 'pppds'
plot(pppds, qi_name = "pr", n_breaks = 50,
  log_scale = FALSE, upper = NULL, lower = NULL,
  plot_matrix_layout = NULL, arrow_ht = 0.2, ...)

Arguments

pppds	An object of class pppds, created by the function combine_pppd().
qi_name	The name of the quantity of interest to plot. Defaults to "pr". The other options are "fd" and "rr". A single number giving the number of cells for the histogram. Defaults to 50. For examining the partial prior predictive distritution, too many breaks are preferable to too few. A character string naming an algorithm to compute the number of cells. See documentation for hist() for details and other algorithms. A vector giving the breakpoints between histogram cells. A function to compute the vector of breakpoints. A function to compute the number of cells.
log_scale	Logical; should the quantity of interest be plotted on the log scale? Defaults to FALSE. I recommend setting to TRUE if the distribution has a long right tail, as can happen with risk-ratios in certain situations.
upper	The upper bound of quantity of interest to plot.
lower	The lower bound of quantity of interest to plot.
plot_matrix_layout	A vector of the form c(n_row, n_col) to indicate the number of rows and the number of columns in the plot matrix. Defaults to a single row.
arrow_ht	The height of the information about truncation. Defaults to 0.2. The bottom of the plot is 0.0 and the top is 1.0.
...	Arguments passed to compact_hist().

Details

Plots a histograms using the compact axis notation from the compactr package.

carlislerainey/separation documentation built on May 13, 2019, 12:45 p.m.