plot.posts: Plots densities of model coefficients using the compact axis...

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

Description

plot.posts() plots densities of model coefficients using the compact axis notation from the compactr package.

Usage

## S3 method for class 'posts'
plot(posts, var_name, ci_type = "hpd", prob = 0.9,
  plot_matrix_layout = NULL, xlim = NULL, ylim = NULL, ...)

Arguments

posts	An object of class pppds, created by the function combine_post().
var_name	The name variable for the coefficient to plot.
ci_type	The type of confidence interval to compute. Either "hpd" (highest posterior density) or "et" (equal-tailed). Defaults to "hpd".
prob	A numeric scalar in the interval (0,1) giving the target probability content of the intervals.
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.
xlim	The x limits (x1, x2) of the plot.
ylim	The y limits (y1, y2) of the plot.
...	Arguments passed to eplot() in the package compactr.

Details

Plots densities of model coefficients

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