sobol {BASS} | R Documentation |

## BASS Sensitivity Analysis

### Description

Decomposes the variance of the BASS model into variance due to main effects, two way interactions, and so on, similar to the ANOVA decomposition for linear models. Uses the Sobol' decomposition, which can be done analytically for MARS models.

### Usage

```
sobol(
bassMod,
prior = NULL,
prior.func = NULL,
mcmc.use = NULL,
func.var = NULL,
xx.func.var = NULL,
verbose = TRUE,
getEffects = FALSE
)
```

### Arguments

`bassMod` |
a fitted model output from the |

`prior` |
a list of priors; uniform, truncated mixture of Normals or Ts for continuous; vector of category weights for categorical. Default is uniform over range of data. |

`prior.func` |
prior for functional variable. In almost all cases, keep this as the uniform default. |

`mcmc.use` |
an integer vector indexing which MCMC iterations to use for sensitivity analysis. |

`func.var` |
an integer indicating which functional variable to make sensitivity indices a function of. Disregard if |

`xx.func.var` |
grid for functional variable specified by |

`verbose` |
logical; should progress be displayed? |

`getEffects` |
logical; should Sobols ANOVA decomposition be computed? |

### Details

Performs analytical Sobol' decomposition for each MCMC iteration in mcmc.use (each corresponds to a MARS model), yeilding a posterior distribution of sensitivity indices. Can obtain Sobol' indices as a function of one functional variable.

### Value

If non-functional (`func.var = NULL`

), a list with two elements:

`S` |
a data frame of sensitivity indices with number of rows matching the length of |

`T` |
a data frame of total sensitivity indices with number of rows matching the length of |

Otherwise, a list with four elements:

`S` |
an array with first dimension corresponding to MCMC samples (same length as |

`S.var` |
same as |

`names.ind` |
a vector of names of the main effects and interactions used. |

`xx` |
the grid used for the functional variable. |

### See Also

bass for model fitting and predict.bass for prediction.

### Examples

```
# See examples in bass documentation.
```

*BASS*version 1.3.1 Index]