localProcedure {bartMan} | R Documentation |

## localProcedure

### Description

A variable selection approach performed by permuting the response.

### Usage

```
localProcedure(
model,
data,
response,
numRep = 10,
numTreesRep = NULL,
alpha = 0.5,
shift = FALSE
)
```

### Arguments

`model` |
Model created from either the BART, dbarts or bartMachine packages. |

`data` |
A data frame containing variables in the model. |

`response` |
The name of the response for the fit. |

`numRep` |
The number of replicates to perform for the BART null model's variable inclusion proportions. |

`numTreesRep` |
The number of trees to be used in the replicates. As suggested by Chipman (2009), a small number of trees is recommended (~20) to force important variables to used in the model. If NULL, then the number of trees from the true model is used. |

`alpha` |
The cut-off level for the thresholds. |

`shift` |
Whether to shift the inclusion proportion points by the difference in distance between the quantile and the value of the inclusion proportion point. |

### Value

A variable selection plot using the local procedure method.

### Examples

```
if(requireNamespace("dbarts", quietly = TRUE)){
# Load the dbarts package to access the bart function
library(dbarts)
# Get Data
df <- na.omit(airquality)
# Create Simple dbarts Model For Regression:
set.seed(1701)
dbartModel <- bart(df[2:6], df[,1], ntree = 5, keeptrees = TRUE, nskip = 10, ndpost = 10)
localProcedure(model = dbartModel,
data = df,
numRep = 5,
numTreesRep = 5,
alpha = 0.5,
shift = FALSE)
}
```

*bartMan*version 0.1.1 Index]