.J_RJMCMC: RJMCMC (with Bayesian Borrowing)

Description

Metropolis-Hastings Green Reversible Jump move, with Bayesian Borrowing

Usage

.J_RJMCMC(
  df_hist,
  df_curr,
  Y,
  Y_0,
  I,
  I_0,
  X,
  X_0,
  lambda,
  lambda_0,
  beta,
  beta_0,
  mu,
  sigma2,
  tau,
  s,
  J,
  Jmax,
  bp,
  bp_0,
  clam_smooth,
  a_tau = NULL,
  b_tau = NULL,
  c_tau = NULL,
  d_tau = NULL,
  type,
  p_0 = NULL,
  phi,
  pi_b,
  maxSj
)

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_hist: data_frame containing historical data.
df_curr: data_frame containing current trial data.
Y: data.
Y_0: historical data.
I: censoring indicator.
I_0: historical trial censoring indicator.
X: design matrix.
X_0: historical trial design matrix.
lambda: baseline hazard.
lambda_0: historical trial baseline hazard.
beta: current trial parameters.
beta_0: historical trial parameters.
mu: prior mean for baseline hazard.
sigma2: prior variance hyperparameter for baseline hazard.
tau: borrowing parameter.
s: split point locations, J + 2.
J: number of split points.
Jmax: maximum number of split points.
bp: number of covariates in current trial.
bp_0: number of covariates in historical trial.
clam_smooth: neighbor interactions, in range (0, 1), for ICAR update.
a_tau: tau hyperparameter.
b_tau: tau hyperparameter.
c_tau: tau hyperparameter.
d_tau: tau hyperparameter.
type: choice of borrowing, "mix", "uni", or any other string for borrowing on every baseline hazard without mixture.
p_0: mixture ratio.
phi: J hyperparameter.
pi_b: probability of birth move.
maxSj: maximal time point, either current or historic.