AFcorMI | R Documentation |

AFcorMI computes a predicted weighted mutual information adjacency matrix from a given correlation matrix.

```
AFcorMI(r, m)
```

`r` |
a symmetric correlation matrix with values from -1 to 1. |

`m` |
number of observations from which the correlation was calcuated. |

This function is a one-to-one prediction when we consider correlation as unsigned. The prediction
corresponds to the `AdjacencyUniversalVersion2`

discussed in the help file for the function
`mutualInfoAdjacency`

. For more information
about the generation and features of the predicted mutual information adjacency, please refer to the function
`mutualInfoAdjacency`

.

A matrix with the same size as the input correlation matrix, containing the predicted mutual information of
type `AdjacencyUniversalVersion2`

.

Steve Horvath, Lin Song, Peter Langfelder

`mutualInfoAdjacency`

```
#Simulate a data frame datE which contains 5 columns and 50 observations
m=50
x1=rnorm(m)
r=.5; x2=r*x1+sqrt(1-r^2)*rnorm(m)
r=.3; x3=r*(x1-.5)^2+sqrt(1-r^2)*rnorm(m)
x4=rnorm(m)
r=.3; x5=r*x4+sqrt(1-r^2)*rnorm(m)
datE=data.frame(x1,x2,x3,x4,x5)
#calculate predicted AUV2
cor.data=cor(datE, use="p")
AUV2=AFcorMI(r=cor.data, m=nrow(datE))
```

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