h | R Documentation |
Function to specify a hierarchical component within a Bayesian model specification
h(..., model, parentSuffix = "", effName = NULL)
... |
Named arguments to be passed to the hierarchical model specification |
model |
Either a character scalar giving the name of the natively-supported hierarchical model to apply or a function implementing the hierarchical model |
parentSuffix |
A character scalar giving an additional suffix applied to
all elements created in the hierarchical model specification. This argument
is rarely set directly by the user but by the model definition functions
(such as |
effName |
A character scalar giving a name for the hierarchical effect being defined and used as name for the appropriate nodes |
A list element with the following named elements:
name
A character scalar containing the name of the hierarchical effect and is used as a name for intermediary variables
code
A character scalar containing the NIMBLE code specifying
the hierarchical effect (and will be passed to
nimbleCode
)
constants
A list containing named elements corresponding to
the variables used as constants needed for the hierarchical effect in
nimbleModel
data
A list containing named elements corresponding to the
data nodes used for the hierarchical effect in
nimbleModel
inits
A named list of starting values for model variables used
in the hierarchical effect and passed to nimbleModel
monitors
The nodes of the hierarchical effect to
monitor in the MCMC and passed to configureMCMC
monitors2
The nodes of the hierarchical effect to
monitor in the supplemental chain monitor in the MCMC and passed to
configureMCMC
initCode
A list of language objects to run upon initialisation
of the NIMBLE instance (see mcmcNIMBLERun
)
exitCode
A list of language objects to run upon completion of
the NIMBLE instance (see mcmcNIMBLERun
)
runTimeGlobal
A list of objects to pass to be compied into
each environment of each NIMBLE instance (see mcmcNIMBLERun
)
projFunc
A function as produced by the
nimbleFunction
function that maps the random variables
defined by the hierarchical model to the data. If NULL
then it is
assumed the effect is defined with the same structure as the data already
Joseph D. Chipperfield, joechip90@googlemail.com
nimbleCode
, mcmcNIMBLERun
,
configureMCMC
, nimbleFunction
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