plot_coefs: Posterior predictive check for walker object

In walker: Bayesian Generalized Linear Models with Time-Varying Coefficients

Posterior predictive check for walker object

Description

Plots sample quantiles from posterior predictive sample. See bayesplot::ppc_ribbon() for details.

Usage

plot_coefs(
  object,
  level = 0.05,
  alpha = 0.33,
  transform = identity,
  scales = "fixed",
  add_zero = TRUE
)

Arguments

object	An output from walker().
level	Level for intervals. Default is 0.05, leading to 90% intervals.
alpha	Transparency level for ggplot2::geom_ribbon().
transform	Optional vectorized function for transforming the coefficients (for example exp).
scales	Should y-axis of the panels be "fixed" (default) or "free"?
add_zero	Logical, should a dashed line indicating a zero be included?

walker documentation built on Sept. 11, 2024, 8:33 p.m.