.shuffle_split_point_location {BayesFBHborrow} | R Documentation |

## Metropolis Hastings step: shuffle the split point locations (with Bayesian borrowing)

### Description

Metropolis Hastings step: shuffle the split point locations (with Bayesian borrowing)

### Usage

```
.shuffle_split_point_location(
df_hist,
df_curr,
Y_0,
I_0,
X_0,
lambda_0,
beta_0,
Y,
I,
X,
lambda,
beta,
s,
J,
bp_0,
bp,
clam_smooth,
maxSj
)
```

### Arguments

`df_hist` |
dataframe containing historical trial data and parmaeters |

`df_curr` |
data.frame containing current trial data and parameters |

`Y_0` |
historical trial data |

`I_0` |
historical trial censoring indicator |

`X_0` |
historical trial design matrix |

`lambda_0` |
historical baseline hazard |

`beta_0` |
historical parameter vector |

`Y` |
data |

`I` |
censoring indicator |

`X` |
design matrix |

`lambda` |
baseline hazard |

`beta` |
parameter vector |

`s` |
split point locations, J + 2 |

`J` |
number of split points |

`bp_0` |
number of covariates in historical trial |

`bp` |
number of covariates in current trial |

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

`maxSj` |
the smallest of the maximal time points, min(max(Y), max(Y_0)) |

### Value

list containing new split points, updated Sigma_s and data.frames for historic and current trial data

*BayesFBHborrow*version 2.0.1 Index]