simconf.inla: Simultaneous confidence regions for latent Gaussian models

In excursions: Excursion Sets and Contour Credibility Regions for Random Fields

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,
  link = FALSE,
  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.
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.
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.
ind	If only a part of a component should be used in the calculations, this argument specifies the indices for that part.
alpha	Error probability for the region.
method	Method for handling the latent Gaussian structure: 'EB' Empirical Bayes (Gaussian approximation of posterior). 'NI' Numerical integration (Calculation based on the Gaussian mixture approximation of the posterior, as calculated by INLA).
n.iter	Number or iterations in the MC sampler that is used for approximating probabilities. The default value is 10000.
verbose	Set to TRUE for verbose mode (optional).
link	Transform output to the scale of the data using the link function as defined in the model estimated with INLA (default FALSE).
max.threads	Decides the number of threads the program can use. Set to 0 for using the maximum number of threads allowed by the system (default).
seed	Random seed (optional).
inla.sample	Set to TRUE if inla.posterior.sample should be used for the MC integration.

Details

See simconf for details.

Value

An object of class "excurobj" with elements

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.

Note

This function requires the INLA package, which is not a CRAN package. See https://www.r-inla.org/download-install for easy installation instructions.

Author(s)

David Bolin [e-mail]

References

Bolin et al. (2015) Statistical prediction of global sea level from global temperature, Statistica Sinica, vol 25, pp 351-367.

Bolin, D. and Lindgren, F. (2018), Calculating Probabilistic Excursion Sets and Related Quantities Using excursions, Journal of Statistical Software, vol 86, no 1, pp 1-20.

See Also

simconf, simconf.mc, simconf.mixture

Examples

## Not run: 
if (require.nowarnings("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,
      return.marginals.predictor = TRUE
    ),
    num.threads = "1:1"
  )

  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")
}

## End(Not run)

excursions documentation built on Oct. 23, 2023, 5:07 p.m.