excursions (version 2.0.6)

simconf.inla: Simultaneous confidence regions for latent Gaussian models

Description

simconf.inla is used for calculating simultaneous confidence regions for latent Gaussian models estimated using INLA.

Usage

simconf.inla(result.inla,
             stack,
             name=NULL,
             tag=NULL,
             ind=NULL,
             alpha,
             method="NI",
             n.iter=10000,
             verbose=0,
             max.threads=0,
             seed=NULL,
             inla.sample=TRUE)

Arguments

result.inla

Result object from INLA call

stack

The stack object used in the INLA call.

tag

The tag of the component in the stack for which to do the calculation. This argument should only be used if a stack object is provided, use the name argument otherwise.

name

The name of the component for which to do the calculation. This argument should only be used if a stack object is not provided, use the tag argument otherwise.

ind

If only a part of a component should be used in the calculations, this argument specifies the indices for that part.

method

Method for handeling the latent Gaussian structure:

• 'EB'

{Empirical Bayes (Gaussian approximation of posterior)} 'NI'{Numerical integration (Calculation based on the Gaussian mixture approximation of the posterior,

Value

• A list:
• a
  The lower bound.
• b
  The upper bound.
• a.marginal
  The lower bound for pointwise confidence bands.
• b.marginal
  The upper bound for pointwise confidence bands.

item

• alpha
• n.iter
• verbose
• max.threads
• seed
• inla.sample

Examples

if (require(INLA)) {
n <- 10
x <- seq(0, 6, length.out=n)
y <- sin(x) + rnorm(n)
mu <- 1:n

result <- inla(y ~ 1 + f(mu, model='rw2'),
               data=list(y=y, mu=mu), verbose=FALSE,
               control.compute = list(config=TRUE),
               num.threads = 1)

res <- simconf.inla(result, name='mu', alpha = 0.05, max.threads = 1)

plot(result$summary.random$mu$mean,ylim=c(-2,2))
lines(res$a)
lines(res$b)
lines(res$a.marginal,col="2")
lines(res$b.marginal,col="2")
}