methods: Methods to work with a 'model'.

In INLAtools: Functionalities for the 'INLA' Package

Methods to work with a model.

Description

For a given model object query the initial, mu, log prior, graph or precision prec can be evaluated/retrieved.

Usage

initial(model)

mu(model, theta)

prior(model, theta)

graph(model, optimize)

prec(model, theta, optimize)

## Default S3 method:
prec(model, ...)

## S4 method for signature 'Matrix'
vcov(object, ...)

## S3 method for class 'inla'
prec(model, ...)

Arguments

model	object to represent a model
theta	numeric vector. For prior it can be a numeric matrix, with number of lines equal the size of theta and each column as a different case.
optimize	logical indicating if it is to be returned only the elements and not as a sparse matrix.
...	additional arguments passed on
object	Matrix supposed to be a sparse precision matrix

Value

the result of the desired query of the 'cgeneric' model. 'graph' and 'prec' can be either a vector (if optimize = TRUE) or a sparse matrix.

Functions

• initial(): Retrieve the initial model parameter(s)

• mu(): Evaluate the model's mean

• prior(): Evaluate the log-prior for a given theta

• graph(): Retrieve the models' graph

• prec(): Retrieve the precision for a given theta

• prec(default): The default precision method computes the inverse of the variance

• vcov(Matrix): The vcov method for sparse matrices

• prec(inla): Define the prec method for an inla output object

See Also

prior.cgeneric()

INLAtools documentation built on June 23, 2025, 5:09 p.m.