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 onerelational onemode or twomode networks.
Usage
RF(res, m = 10, loops = NULL)
Arguments
res 
An object returned by the function 
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), 13151335. doi:10.1007/s10260021005951
See Also
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[1] * tclu[1], mean = 0, sd = 1)
net[clu == 1, clu == 2] < rnorm(n = tclu[1] * tclu[2], mean = 4, sd = 1)
net[clu == 2, clu == 1] < rnorm(n = tclu[2] * tclu[1], mean = 0, sd = 1)
net[clu == 2, clu == 2] < rnorm(n = tclu[2] * tclu[2], 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)