logLik.ghype

Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG).
To learn how to use it, check the vignettes for a quick tutorial.
Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300>
together with those relevant references from the one listed below.
The package is based on the research developed at the Chair of Systems Design, ETH Zurich.
Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <doi:10.48550/arXiv.1607.02441>.
Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>.
Casiraghi, G., (2017) <doi:10.48550/arXiv.1702.02048>.
Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926>.
Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>.
Casiraghi, G., Nanumyan, V. (2021) <doi:10.1038/s41598-021-92519-y>.
Casiraghi, G. (2021) <doi:10.1088/2632-072X/ac0493>.

Giona Casiraghi

ghypernet

Fit and Simulate Generalised Hypergeometric Ensembles of Graphs

Vahan Nanumyan

Laurence Brandenberger

Giacomo Vaccario

logLik.ghype function

<dl><dt>object</dt>
<dd>ghype model.</dd>
<dt>...</dt>
<dd>additional arguments passed to and from internal methods.</dd></dl>

Arguments

Extract Log-Likelihood — logLik.ghype

<dl>

<dt>object</dt>
<dd>ghype model.</dd>


<dt>...</dt>
<dd>additional arguments passed to and from internal methods.</dd>

</dl>

logLik.ghype: Extract Log-Likelihood

Description

Usage

Value

Arguments