sim.adaptiveGMRF2COVAR {adaptsmoFMRI} | R Documentation |

## Adaptive GMRF Model for Simulated Data

### Description

This function estimates the effects of a synthetic spatiotemporal data set resembling functional MR Images (fMRI), with the method of efficient Markov Chain Monte Carlo (MCMC) simulation. The Metropolis Hastings (MH) algorithm is used for the non-approximate case and the Gibbs sampler for the approximate case.

### Usage

```
sim.adaptiveGMRF2COVAR(data, hrf, approximate = FALSE, K
= 500, a = 1, b = 1, c = 1, d = 1, nu = 1, block = 1,
burnin = 1, thin = 1)
```

### Arguments

`data` |
simulated fMRI-data, needs to be an array of
dimension |

`hrf` |
haemodynamic response function, needs to be a
vector of length |

`approximate` |
logical, if |

`K` |
scalar, length of the MCMC path, hence iteration steps. |

`a` |
scalar, shape hyperparameter of the
inverse-gamma distribution of the variance parameter
( |

`b` |
scalar, scale hyperparameter of the inverse
gamma distribution of the variance parameter
( |

`c` |
scalar, shape hyperparameter of the inverse
gamma distribution of the precision parameter
( |

`d` |
scalar, scale hyperparameter of the inverse
gamma distribution of the precision parameter
( |

`nu` |
scalar, shape and scale hyperparameter of the
gamma distribution of the interaction weights
( |

`block` |
scalar, when |

`burnin` |
scalar, defining the first iteration steps which should be omitted from MCMC path. |

`thin` |
scalar, only every |

### Value

`dx` |
scalar, number of pixels in x-direction. |

`dy` |
scalar, number of pixels in y-direction. |

`I` |
scalar, number of pixels. |

`iter` |
scalar, number of MCMC iterations. |

`coord` |
matrix, coordinates of pixels. |

`nei` |
matrix, locations of weights in precision matrix. |

`NEI` |
scalar, number of weights. |

`beta.out` |
matrix, MCMC path of covariates. |

`w.out` |
matrix, MCMC path of weights. |

`sigma.out` |
matrix, MCMC path of variance parameters. |

`tauk.out` |
matrix, MCMC path of hyper parameters. |

### Note

This function is solely for two covariates.

### Author(s)

Maximilian Hughes

### Examples

```
# See example function for simulated data (one covariate).
```

*adaptsmoFMRI*version 1.2 Index]