plot.shrinkDSM: Graphical summary of posterior distribution of fitted dynamic...

In shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage

Graphical summary of posterior distribution of fitted dynamic survival model

Description

plot.shrinkDSM generates plots visualizing the posterior distribution estimated as a result from a call to shrinkDSM.

Usage

## S3 method for class 'shrinkDSM'
plot(
  x,
  pars = c("beta"),
  nplot = 3,
  h_borders = c(0.05, 0.05),
  w_borders = c(0.02, 0.02),
  ...
)

Arguments

x	a shrinkDSM object.
pars	a character vector containing the names of the parameters to be visualized. The names have to coincide with the names of the list elements of the shrinkDSM object. Throws an error if any element of pars does not fulfill this criterium. The default is c("beta").
nplot	positive integer that indicates the number of tvp plots to display on a single page before a new page is generated. The default value is 3.
h_borders	single real, positive number smaller than 0.5 or a vector containing two such numbers. Determines the relative amount of space (the total amount summing up to 1) left blank on the left and right of the plot, in that order. The default is c(0.05, 0.05).
w_borders	single real, positive number smaller than 0.5 or a vector containing two such numbers. Determines the relative amount of space (the total amount summing up to 1) left blank at the top and bottom of the plot, in that order. The default is c(0.02, 0.02).
...	further arguments to be passed to the respective plotting functions.

Value

Called for its side effects and returns invisibly.

Author(s)

Peter Knaus [e-mail]

See Also

Other plotting functions: plot.mcmc.dsm.tvp(), plot.shrinkDSM_pred()

Examples

set.seed(123)
data("gastric")

# Create intervals for piecewise exponential model
intervals <- divisionpoints(gastric$time, gastric$status, 2)

# Estimate model
mod <- shrinkDSM(time ~ radiation, gastric,
                 delta = gastric$status, S = intervals)
plot(mod)


# Will produce an error because 'hello' is not a parameter in the model
## Not run: 
plot(mod, pars = c("beta", "hello"))

## End(Not run)

shrinkDSM documentation built on Nov. 16, 2022, 1:11 a.m.