This document describes the process by which ergm
and
related packages select the MCMC proposal for a particular analysis.
Note that it is not intended to be a tutorial as much as a description
of what inputs and outputs different parts of the system expect. Nor
does it cover the C API.
There is a number of factors that can affect MCMC sampling, some of them historical and some of them new:
functions and other structures defined in an accessible namespace
ergm_proposal_table()
a function that if called with no
arguments returns a table of registered proposals and updates it
otherwise. See ? ergm_proposal_table
for documentation and
the meaning of its columns. Of particular interest is its
Constraints
column, which encodes which constraints the
proposal does (always) enforce and which it
can enforce.InitErgmReference.<REFERENCE>
a family of
initializers for the reference distribution. For the purposes of the
proposal selection, among its outputs should be $name
specifying the name of the reference distribution.InitErgmConstraint.<CONSTRAINT>
a family of
initializers for constraints, weightings, and other high-level
specifiers of the proposal distribution. Hard constraints, probabilistic
weights, and hints all use this API. For the purposes of the proposal
selection, its outputs include
$constrain
(defaulting to
<CONSTRAINT>
) a character vector specifying which
constraints are enforced, and can include several semantically nested
elements;$dependence
(defaulting to TRUE
)
specifying whether the constraint is dyad-dependent;$priority
(defaulting to Inf
) specifying
how important it is that the constraint is met (with Inf
meaning that it must be met); and$implies
/$impliedby
specifying which other
constraints this constraint enforces or is enforced by, and this can
include itself for constraints, such as edges
that can only
be applied once.$free_dyads
either an RLEBDM or a function with no
arguments that returns an RLEBDM specifying which dyads are not
constrained by this constraint.arguments and settings passed to the call or as control parameters.
constraints=
argument (top-level): A one-sided formula
containing a +
- or -
-separated list of
constraints. +
terms add additional constraints to the
model whereas -
constraints relax them. -
constraints are primarily used internally observational process
estimation and are not described in detail, except to note that 1) they
must be dyad-independent and 2) they necessitate falling back to the
RLEBDM sampling API.reference=
argument (top-level): A one-sided formula
specifying the ERGM reference distribution, usually as a name with
parameters if appropriate.control$MCMC.prop=
control parameter: A formula whose
RHS containing +
-separated “hints” to the sampler; an
optional LHS may contain the proposal name directly.control$MCMC.prop.weights=
control parameter: A string
selecting proposal weighting (probably deprecated)control$MCMC.prop.args=
control parameter: A list
specifying information to be passed to the proposalMost of this is implemented in the
ergm_proposal.formula()
method:
InitErgmReference.<REFERENCE>
is called with
arguments of reference=
’s LHS, obtaining the name of the
reference.InitErgmConstraint.<CONSTRAINT>
function is called
and their outputs are stored in a list of initialized constraints (an
ergm_conlist
object). .dyads
pseudo-constraint
is added to dyad-independent constraints (not to hints with
$priority < Inf
). For hints, $dependence
element is overwritten to FALSE
. The list is named, with
the name taken from the first element of the $constrains
.
constraints=
MCMC.prop=
$implies
/$impliedby
settings.ergm_proposal_table()
are filtered by Class
, Reference
,
Weights
(if MCMC.prop.weights
differs from
"default"
), and Proposal
(if the LHS of
MCMC.prop
is provided).priority==Inf
, it is discarded.priority<Inf
and that the proposal
doesn’t and can’t enforce, its
(innate, specified in the column of the
ergm_proposal_table()
) Priority
value is
penalised by the priority
of that constraint.InitErgmProposal.*
functions are attempted. If
a call returns NULL
, next proposal is attempted. (This can
be useful if a proposal handles a particular special case that is not
accounted for by constraints.)