BayesFBHborrow (version 2.0.2)

.J_RJMCMC_NoBorrow: RJMCMC (without Bayesian Borrowing)

Description

Metropolis-Hastings Green Reversible Jump move, without Bayesian Borrowing

Usage

.J_RJMCMC_NoBorrow(
  df,
  Y_0,
  I_0,
  X_0,
  lambda_0,
  beta_0,
  mu,
  sigma2,
  s,
  J,
  Jmax,
  bp_0,
  clam_smooth,
  phi,
  pi_b
)

Value

list of proposed J and s, with adjusted values of lambda, lambda_0, tau, Sigma_s, and data_frames for historical and current trial data

Arguments

df

data_frame

Y_0

data

I_0

censoring indicator

X_0

design matrix

lambda_0

baseline hazard

beta_0

historical trial parameters

mu

prior mean for baseline hazard

sigma2

prior variance hyperparameter for baseline hazard

s

split point locations, J + 2

J

number of split points

Jmax

maximum number of split points

bp_0

number of covariates in historical trial

clam_smooth

neighbor interactions, in range (0, 1), for ICAR update

phi

J hyperparameter

pi_b

probability of birth move