Description Usage Arguments Value Methods (by class) Examples
General method to compute loglikelihood for ghype models.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34  logl(
object,
xi = NULL,
omega = NULL,
directed = NULL,
selfloops = NULL,
adj = NULL,
multinomial = NULL,
...
)
## S3 method for class 'ghype'
logl(
object,
xi = NULL,
omega = NULL,
directed = NULL,
selfloops = NULL,
adj = NULL,
multinomial = NULL,
...
)
## S3 method for class 'matrix'
logl(
object,
xi = NULL,
omega = NULL,
directed = NULL,
selfloops = NULL,
adj = NULL,
multinomial = NULL,
...
)

object 
either an adjacency matrix or ghype model If a ghype model is passed, then 'xi', 'omega', 'directed', 'selfloops' are ignored If an adjacency matrix is passed, then 'adj' is ignored 
xi 
matrix, combinatorial matrix to build ghype model, considered only if object is an adjacency matrix 
omega 
matrix, propensity matrix to build ghype model, considered only if object is an adjacency matrix 
directed 
boolean, is ghype model directed? considered only if object is an adjacency matrix 
selfloops 
boolean, has ghype model selfloops? considered only if object is an adjacency matrix 
adj 
optional matrix, adjacency matrix of which to compute loglikelihood, considered only if object is ghype model If adj is not passed, and object is a ghype model, the loglikelihood is computed for the original adjacency matrix stored in object. 
multinomial 
optional boolean. Force multinomial approximation? If not chosen, multinomial chosen for large graphs. 
... 
additional parameters passed to and from internal methods 
loglikelihood value
ghype
: Computes loglikelihood for ghype models from model object
matrix
: Computes loglikelihood for ghype models from adjacency.
1 2 3 4 5 6  data('adj_karate')
model < scm(adj_karate, FALSE, FALSE)
logl(object = model)
new_adj < adj_karate
new_adj[3,4] < 10
logl(object=model, adj=new_adj)

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