# Network Difference

### Description

Returns the difference of the input matrices. Output object is an
adjacency matrix where edges present in `matrix1`

but not `matrix2`

are returned. The edge value is maintained provided `cutoff`

= NULL.
Edges in both graphs failing to meet the `cutoff`

, if provided, are set
to zero before taking the graph difference.

### Usage

1 |

### Arguments

`matrix1` |
Square matrix (e.g. correlation or adjacency) containing row/column labels |

`matrix2` |
Square matrix (e.g. correlation or adjacency) containing row/column labels |

`cutoff` |
The cutoff value. Edges less than this value (absolute value considered)are converted to zero. |

`...` |
Other parameters. |

### Details

Matrices must be square and have row and column labels. Output adjacency matrix can be used directly for creating a graph object.

### Value

`netDiff`

returns an adjacency matrix containing edges present in
`matrix1`

that are not present in `matrix2`

. Edges below
`cutoff`

are set to zero.

### Author(s)

Shannon M. Bell

### Examples

1 2 3 4 5 6 7 8 9 10 11 | ```
#using the state.x77 and USArrest datasets
#remove data from states for illustration
ssArrest<-subset(t(USArrests), select=-c(Alabama,Colorado,Delaware))
ssState<-subset(t(state.x77), select=-c(Alabama, Arizona, Iowa))
arrestCor<-cor(ssArrest)
stateCor<-cor(ssState)
dataDiff<-netDiff(stateCor, arrestCor)
dataDiff[1:15,1:5]
#Setting a cutoff to remove any edges that are below 0.6
dataDiff.6<-netDiff(stateCor, arrestCor, cutoff=0.6)
dataDiff.6[1:15,1:5]
``` |