SCCcomp: Example SCC Computation Result

In neuroSCC: Bridging Simultaneous Confidence Corridors and PET Neuroimaging

Example SCC Computation Result

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 ImageSCC::scc.image function and represents a realistic output from SCC-based neuroimaging group comparisons.

This dataset is used in the examples of getPoints and calculateMetrics, allowing users to explore SCC outputs without needing to recompute them.

Usage

data("SCCcomp")

Format

A named list of class "image" with the following elements

scc

3D array of SCC confidence bands, dimensions [n, 2, alpha].

Z.band

Matrix of grid coordinates corresponding to evaluated locations.

ind.inside.cover

Integer vector of indices for grid points inside the SCC band.

V.est.a, V.est.b

Vertex matrices for triangulated domains (pathological and control groups).

Tr.est.a, Tr.est.b

Triangle index matrices corresponding to the domain meshes.

alpha

Vector of confidence levels used (e.g., 0.1, 0.05, 0.01).

d.est

Spline degree used in mean function estimation.

r

Smoothing parameter used during fitting.

Source

Simulated PET neuroimaging study for evaluating SCC methodology.

See Also

getPoints, calculateMetrics, ImageSCC::scc.image

neuroSCC documentation built on April 4, 2025, 3:50 a.m.