altkstar-ergmTerm-201bf7a6: Alternating k-star

In statnet/ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks

Alternating k-star

Description

Add one network statistic to the model equal to a weighted alternating sequence of k-star statistics with weight parameter lambda.

Usage

# binary: altkstar(lambda,
#                 fixed=FALSE)

Arguments

lambda	weight parameter to model
fixed	indicates whether the decay parameter is fixed at the given value, or is to be fit as a curved exponential family model (see Hunter and Handcock, 2006). The default is FALSE, which means the scale parameter is not fixed and thus the model is a CEF model.

Details

This is the version given in Snijders et al. (2006). The gwdegree and altkstar produce mathematically equivalent models, as long as they are used together with the edges (or kstar(1)) term, yet the interpretation of the gwdegree parameters is slightly more straightforward than the interpretation of the altkstar parameters. For this reason, we recommend the use of the gwdegree instead of altkstar. See Section 3 and especially equation (13) of Hunter (2007) for details.

Note

This term can only be used with undirected networks.

See Also

ergmTerm for index of model terms currently visible to the package.

\Sexpr[results=rd,stage=render]{ergm:::.formatTermKeywords("ergmTerm", "altkstar", "subsection")}

statnet/ergm documentation built on April 17, 2024, 12:21 p.m.