| .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]