% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SCCcomp.R
\docType{data}
\name{SCCcomp}
\alias{SCCcomp}
\title{Example SCC Computation Result}
\format{
A named list of class \code{"image"} with the following elements
\describe{
  \item{\code{scc}}{3D array of SCC confidence bands, dimensions \code{[n, 2, alpha]}.}
  \item{\code{Z.band}}{Matrix of grid coordinates corresponding to evaluated locations.}
  \item{\code{ind.inside.cover}}{Integer vector of indices for grid points inside the SCC band.}
  \item{\code{V.est.a}, \code{V.est.b}}{Vertex matrices for triangulated domains (pathological and control groups).}
  \item{\code{Tr.est.a}, \code{Tr.est.b}}{Triangle index matrices corresponding to the domain meshes.}
  \item{\code{alpha}}{Vector of confidence levels used (e.g., 0.1, 0.05, 0.01).}
  \item{\code{d.est}}{Spline degree used in mean function estimation.}
  \item{\code{r}}{Smoothing parameter used during fitting.}
}
}
\source{
Simulated PET neuroimaging study for evaluating SCC methodology.
}
\usage{
data("SCCcomp")
}
\description{
A precomputed example of a Simultaneous Confidence Corridor (SCC) analysis
comparing a group of pathological subjects against controls. This object was generated
using the \code{ImageSCC::scc.image} function and represents a realistic output
from SCC-based neuroimaging group comparisons.

This dataset is used in the examples of \code{\link{getPoints}} and \code{\link{calculateMetrics}},
allowing users to explore SCC outputs without needing to recompute them.
}
\seealso{
\code{\link{getPoints}}, \code{\link{calculateMetrics}}, \code{ImageSCC::scc.image}
}
\keyword{datasets}
