.J_RJMCMC {BayesFBHborrow}

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
)

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.

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.