rgeneric models

A framework for defining latent models in R

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.iid.model(
  cmd = c("graph", "Q", "mu", "initial", "log.norm.const", "log.prior", "quit"),
  theta = NULL
)

inla.rgeneric.define(
  model = NULL,
  debug = FALSE,
  compile = TRUE,
  optimize = FALSE,
  ...
)

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
)

Arguments

cmd

An allowed request

theta

Values of theta

model

The definition of the model; see inla.rgeneric.ar1.model

debug

Logical. Enable debug output

compile

Logical. Compile the definition of the model or not.

optimize

Logical. With this option TRUE, then model pass only the values of Q and not the whole matrix. Please see the vignette for details and inla.rgeneric.ar1.model.opt for an example.

...

Named list of variables that defines the environment of model

rmodel

The rgeneric model-object, the output of inla.rgeneric.define

Value

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.

Author

Havard Rue hrue@r-inla.org