.shuffle_split_point_location_NoBorrow {BayesFBHborrow} | R Documentation |
Metropolis Hastings step: shuffle the split point locations (without Bayesian borrowing)
Description
Metropolis Hastings step: shuffle the split point locations (without Bayesian borrowing)
Usage
.shuffle_split_point_location_NoBorrow(
df,
Y_0,
I_0,
X_0,
lambda_0,
beta_0,
s,
J,
bp_0,
clam_smooth
)
Arguments
df |
dataframe containing trial data and parameters |
Y_0 |
data |
I_0 |
censoring indicator |
X_0 |
design matrix |
lambda_0 |
baseline hazard |
beta_0 |
parameter vector |
s |
split point locations, J + 2 |
J |
number of split points |
bp_0 |
number of covariates in historical trial |
clam_smooth |
neighbor interactions, in range (0, 1), for ICAR update |
Value
list containing new split points, updated Sigma_s and data.frames for historic and current trial data
[Package BayesFBHborrow version 2.0.1 Index]