ergm.eta:
Operations with 'eta' vector of canonical parameter values from ergm model
Description
The ergm.eta
function calculates and returns eta, mapped from
theta using the etamap object created by ergm.etamap
.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
The ergm.etamap
function takes a model object and creates a mapping
from the model parameters, theta, to the canonical (linear) eta parameters;
the mapping is carried out by ergm.eta
Usage
ergm.eta(theta, etamap)
ergm.etagrad(theta, etamap)
ergm.etagradmult(theta, v, etamap)
ergm.etamap(model)
Arguments
theta
the curved model parameters
etamap
the list of values that constitutes the theta-> eta mapping and is returned by ergm.etamap
v
a vector of the same length as the vector of mapped eta parameters
Value
- for
ergm.eta
: eta
the canonical eta parameters as mapped from theta
- for
ergm.etagrad
: etagrad
a matrix of the gradient of eta
- for
ergm.etagradmult
: ans
the vector that is the product of the gradient of eta and v
; infinite values are replaced by (+-)10000
- for
ergm.etamap
the theta -> eta mapping given by a list of the following:
- canonical : a numeric vector whose ith entry specifies whether
the ith component of theta is canonical (via non-
negative integers) or curved (via zeroes)
- offsetmap : a logical vector whose ith entry tells whether the
ith coefficient of the canonical parameterization
was "offset", i.e fixed
- offset : a logical vector whose ith entry tells whether the
ith model term was offset/fixed
- offsettheta: a logical vector whose ith entry tells whether the
ith curved theta coeffient was offset/fixed;
- curved : a list with one component per curved EF term in the
model containing
- from : the indices of the curved theta parameter that are
to be mapped from
- to : the indices of the canonical eta parameters to be
mapped to
- map : the map provided by
- gradient: the gradient function provided by InitErgmTerm
- cov : the eta covariance ??, possibly always NULL (no
function creates such an item)
- etalength : the length of the eta vector
Details
This function is only 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 sufficient statistics (eta) in the exponential-family model. In non-curved 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.
References
- 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.