RF {blockmodeling} R Documentation

## Calculate the value of the Relative Fit function

### Description

The function calculates the value of the Relative Fit function. Currently implemented only for one-relational one-mode or two-mode networks.

### Usage

RF(res, m = 10, loops = NULL)


### Arguments

 res An object returned by the function optRandomParC. m The number of randomized networks for the estimation of the expected value of a criterion function. It has to be as high as possible. Defaults to 10. loops Whether loops are treated the same as any other values or not.

### Details

The function randomizes an empirical network to compute the value of the Relative Fit function. The networks are randomized in such a way that the values on the links are randomly relocated. Other approaches to randomization also exist and might be more appropriate in some cases, see Cugmas et al. (2021).

### Value

• RF - The value of the Relative Fit function.

• err - The value of a criterion function that is used for blockmodeling (for empirical network).

• rand.err - A vector with the values of the criterion function that is used for blockmodeling (for randomized networks).

### Author(s)

Marjan Cugmas and Aleš Žiberna

### References

Cugmas, M., Žiberna, A., & Ferligoj, A. (2021). The Relative Fit measure for evaluating a blockmodel. Statistical Methods & Applications, 30(5), 1315-1335. doi:10.1007/s10260-021-00595-1

optRandomParC

### Examples

n <- 8 # If larger, the number of partitions increases
# dramatically as does if we increase the number of clusters
net <- matrix(NA, ncol = n, nrow = n)
clu <- rep(1:2, times = c(3, 5))
tclu <- table(clu)
net[clu == 1, clu == 1] <- rnorm(n = tclu * tclu, mean = 0, sd = 1)
net[clu == 1, clu == 2] <- rnorm(n = tclu * tclu, mean = 4, sd = 1)
net[clu == 2, clu == 1] <- rnorm(n = tclu * tclu, mean = 0, sd = 1)
net[clu == 2, clu == 2] <- rnorm(n = tclu * tclu, mean = 0, sd = 1)

res <- optRandomParC(M = net, k = 2, rep = 10, approaches = "hom", homFun = "ss", blocks = "com")
RF(res = res, m = 100, loops = TRUE)


[Package blockmodeling version 1.1.5 Index]