summary.aghq {aghq}R Documentation

Summary statistics computed using AGHQ

Description

The summary.aghq method computes means, standard deviations, and quantiles of the transformed parameter. The associated print method prints these along with diagnostic and other information about the quadrature.

Usage

## S3 method for class 'aghq'
summary(object, ...)

Arguments

object

The return value from aghq::aghq. Summaries are computed for object$transformation$fromtheta(theta).

...

not used.

Value

A list of class aghqsummary, which has a print method. Elements:

See Also

Other quadrature: aghq(), get_hessian(), get_log_normconst(), get_mode(), get_nodesandweights(), get_numquadpoints(), get_opt_results(), get_param_dim(), laplace_approximation(), marginal_laplace_tmb(), marginal_laplace(), nested_quadrature(), normalize_logpost(), optimize_theta(), plot.aghq(), print.aghqsummary(), print.aghq(), print.laplacesummary(), print.laplace(), print.marginallaplacesummary(), summary.laplace(), summary.marginallaplace()

Examples


logfteta2d <- function(eta,y) {
  # eta is now (eta1,eta2)
  # y is now (y1,y2)
  n <- length(y)
  n1 <- ceiling(n/2)
  n2 <- floor(n/2)
  y1 <- y[1:n1]
  y2 <- y[(n1+1):(n1+n2)]
  eta1 <- eta[1]
  eta2 <- eta[2]
  sum(y1) * eta1 - (length(y1) + 1) * exp(eta1) - sum(lgamma(y1+1)) + eta1 +
    sum(y2) * eta2 - (length(y2) + 1) * exp(eta2) - sum(lgamma(y2+1)) + eta2
}
set.seed(84343124)
n1 <- 5
n2 <- 5
n <- n1+n2
y1 <- rpois(n1,5)
y2 <- rpois(n2,5)
objfunc2d <- function(x) logfteta2d(x,c(y1,y2))
funlist2d <- list(
  fn = objfunc2d,
  gr = function(x) numDeriv::grad(objfunc2d,x),
  he = function(x) numDeriv::hessian(objfunc2d,x)
)

thequadrature <- aghq(funlist2d,3,c(0,0))
# Summarize and automatically call its print() method when called interactively:
summary(thequadrature)
# or, compute the summary and save for further processing:
ss <- summary(thequadrature)
str(ss)


[Package aghq version 0.4.1 Index]