Description Usage Arguments Details Value References See Also
The ergm.eta
function calculates and returns eta, mapped
from theta using the etamap
object, usually attached as the
$etamap
element of an ergm_model
object.
The ergm.etagrad
function caculates and returns
the gradient of eta mapped from theta using the etamap object
created by ergm.etamap
. If the gradient is only intended
to be a multiplier for some vector, the more efficient
ergm.etagradmult
is recommended.
The ergm.etagradmult
function calculates and
returns the product of the gradient of eta with a vector v
.
1 2 3 4 5  ergm.eta(theta, etamap)
ergm.etagrad(theta, etamap)
ergm.etagradmult(theta, v, etamap)

theta 
the curved model parameters 
etamap 
the list of values that describes the theta > eta
mapping, usually attached as

v 
a vector of the same length as the vector of mapped eta parameters 
These functions are mainly important in the case of curved exponential family models, i.e., those in which the parameter of interest (theta) is not a linear function of the natural parameters (eta) in the exponentialfamily model. In noncurved models, we may assume without loss of generality that eta(theta)=theta.
A succinct description of how eta(theta) is incorporated into an ERGM is given by equation (5) of Hunter (2007). See Hunter and Handcock (2006) and Hunter (2007) for further details about how eta and its derivatives are used in the estimation process.
For ergm.eta
, the canonical eta parameters as mapped
from theta.
For ergm.etagrad
, a matrix of the gradient of eta
with respect to theta.
For ergm.etagradmult
, the vector that is the product
of the gradient of eta and v
.
Hunter, D. R. and M. S. Handcock (2006). Inference in curved exponential family models for networks. Journal of Computational and Graphical Statistics, 15: 565–583.
Hunter, D. R. (2007). Curved exponential family models for social networks. Social Networks, 29: 216–230.
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