sum_mcmc_bspbss {BSPBSS} | R Documentation |

## Summarization of the MCMC result.

### Description

The function summarizes the MCMC results obtained from `mcmc_bspbss`

.

### Usage

```
sum_mcmc_bspbss(res, X, kernel, start = 1, end = 100, select_prob = 0.8)
```

### Arguments

`res` |
List including MCMC samples, which can be obtained from function |

`X` |
Original data matrix. |

`kernel` |
List including eigenvalues and eigenfunctions of the kernel, see |

`start` |
Start point of the iterations being summarized. |

`end` |
End point of the iterations being summarized. |

`select_prob` |
Lower bound of the posterior inclusion probability required when summarizing the samples of latent sources. |

### Value

List that contains the following terms:

- S
Estimated latent sources.

- pip
Voxel-wise posterior inclusion probability for the latent sources.

- A
Estimated mixing coefficent matrix.

- zeta
Estimated zeta.

- sigma
Estimated sigma.

- logLik
Trace of log-likelihood.

- Slist
MCMC samples of S.

### Examples

```
sim = sim_2Dimage(length = 30, sigma = 5e-4, n = 30, smooth = 6)
ini = init_bspbss(sim$X, sim$coords, q = 3, ker_par = c(0.1,50), num_eigen = 50)
res = mcmc_bspbss(ini$X,ini$init,ini$prior,ini$kernel,n.iter=200,n.burn_in=100,thin=10,show_step=50)
res_sum = sum_mcmc_bspbss(res, ini$X, ini$kernel, start = 11, end = 20, select_p = 0.5)
```

[Package

*BSPBSS*version 1.0.5 Index]