.J_RJMCMC {BayesFBHborrow} | R Documentation |

## 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.

*BayesFBHborrow*version 2.0.1 Index]