proximityMatrix {bartMan} | R Documentation |

## proximityMatrix

### Description

Creates a matrix of proximity values.

### Usage

```
proximityMatrix(trees, nRows, normalize = TRUE, reorder = TRUE, iter = NULL)
```

### Arguments

`trees` |
A list of tree attributes created by 'extractTreeData' function. |

`nRows` |
Number of rows to consider. |

`normalize` |
Default is TRUE. Divide the total number of pairs of observations by the number of trees. |

`reorder` |
Default is TRUE. Whether to sort the matrix so high values are pushed to top left. |

`iter` |
Which iteration to use, if NULL the proximity matrix is calculated over all iterations. |

### Value

A matrix containing proximity values.

### 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)
# Tree Data
trees_data <- extractTreeData(model = dbartModel, data = df)
# Create Proximity Matrix
mProx <- proximityMatrix(trees = trees_data, reorder = TRUE, normalize = TRUE, iter = 1)
}
```

[Package

*bartMan*version 0.1.1 Index]