plot.pppd: Plots a histogram using the compact axis notation from the...

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

Description

plot.pppd() plots a histogram using the compact axis notation from the compactr package.

Usage

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

Arguments

pppd	An object of class pppd, created by the function calc_pppd().
qi_name	The name of the quantity of interest to plot. Defaults to "pr". The other options are "fd" and "rr".
n_breaks	One of the following: 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.
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.
plot	Logical. Should the histgram be plotted? If FALSE, the histogram is not plotted and the data for the histogram are returned.
...	Arguments passed to compact_hist().

Details

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

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