run_jags: Runs a user-supplied JAGS model and returns the output

In kravitz-eli/simCondSurv: What the Package Does (One Line, Title Case)

Description

Runs a user-supplied JAGS model and returns the output

Usage

run_jags(distribution, prop_haz = TRUE, time, event, trt, chains = 2,
  n_iter = 1000L, n_burn = 1000L, n_adapt = 1000L,
  track_variable_names, progress.bar = "none")

Arguments

distribution	Character. name of the distribution of the parametric model
prop_haz	logical. Should a proportional hazards model be fit (TRUE) or a nonproportional hazards model
time	Positive numeric. survival times
event	0/1 variable. Event happened (event = 1) or observation is censored (event = 0)
trt	0/1 variable. Indicates control arm (trt = 0) or experimental arm (trt = 1)
chains	integer number of MCMC chains to run
n_iter	positive integer number of MCMC iterations, default 100,000
n_burn	positive integer length of burn in, default 1,000
n_adapt	number of iterations for adaption in JAGS
track_variable_names	a character vector giving the names of variables to be monitored
progress.bar	should JAGS show a progress bar, "none" (default_), "text" , or "GUI"

Value

a mcmc.list of posterior draws of parameters in track_variable_names, contains matrix of size (n_iter x track_num_variables)

kravitz-eli/simCondSurv documentation built on April 14, 2020, 6:02 a.m.