Adjust Dissolution Component of Network Model Fit — update

Adjusts the dissolution component of a dynamic ERGM fit using the netest function with the edges dissolution approximation method.

Usage

update_dissolution(old.netest, new.coef.diss, nested.edapprox = TRUE)

Arguments

old.netest: An object of class netest, from the netest function.
new.coef.diss: An object of class disscoef, from the dissolution_coefs function.
nested.edapprox: Logical. If edapprox = TRUE the dissolution model is an initial segment of the formation model (see details in netest).

Value

An updated network model object of class netest.

Details

Fitting an ERGM is a computationally intensive process when the model includes dyad dependent terms. With the edges dissolution approximation method of Carnegie et al, the coefficients for a temporal ERGM are approximated by fitting a static ERGM and adjusting the formation coefficients to account for edge dissolution. This function provides a very efficient method to adjust the coefficients of that model when one wants to use a different dissolution model; a typical use case may be to fit several different models with different average edge durations as targets. The example below exhibits that case.

Examples

if (FALSE) { # \dontrun{
nw <- network_initialize(n = 1000)

# Two dissolutions: an average duration of 300 versus 200
diss.300 <- dissolution_coefs(~offset(edges), 300, 0.001)
diss.200 <- dissolution_coefs(~offset(edges), 200, 0.001)

# Fit the two reference models
est300 <- netest(nw = nw,
                formation = ~edges,
                target.stats = c(500),
                coef.diss = diss.300)

est200 <- netest(nw = nw,
                formation = ~edges,
                target.stats = c(500),
                coef.diss = diss.200)

# Alternatively, update the 300 model with the 200 coefficients
est200.compare <- update_dissolution(est300, diss.200)

identical(est200$coef.form, est200.compare$coef.form)
} # }