rgeneric.define {INLA} | R Documentation |
A framework for defining latent models in R
inla.rgeneric.define(model = NULL, debug = FALSE, compile = TRUE, optimize = FALSE, ...) inla.rgeneric.iid.model( cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"), theta = NULL) inla.rgeneric.ar1.model( cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"), theta = NULL) inla.rgeneric.ar1.model.opt( cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"), theta = NULL) inla.rgeneric.wrapper( cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"), model, theta = NULL) inla.rgeneric.q( rmodel, cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"), theta = NULL)
model |
The definition of the model; see |
rmodel |
The rgeneric model-object, the output of |
debug |
Logical. Turn on/off debugging |
compile |
Logical. Compile the definition of the model or not. |
optimze |
Logical. With this option |
cmd |
An allowed request |
theta |
Values of theta |
... |
Named list of variables that defines the environment of |
debug |
Logical. Enable debug output |
This allows a latent model to be
defined in R
.
See inla.rgeneric.ar1.model
and
inla.rgeneric.iid.model
and the documentation for
worked out examples of how to define latent models in this way.
This will be somewhat slow and is intended for special cases and
protyping. The function inla.rgeneric.wrapper
is for
internal use only.
Havard Rue hrue@r-inla.org