data2g.image: Generate simulation examples: two sample case
In funstatpackages/ImageSCC: SCC for Mean Function of Imaging Data

The function generates two-sample simulation data using four different mean functions and eigenfunctions described in the paper.

1 2	data2g.image(na, nb, Z, ind.inside, mu1.func, noise.type = c("Func", "Const"), lam1, lam2, delta, iter = 2019)

`na`	number of images/subjects in the first sample.
`nb`	number of images/subjects in the second sample.
`Z`	a 2-column matrix specifying locations of information.
`ind.inside`	a vector of indices specifying which locations in matrix Z fall inside the irregular domain.
`mu1.func`	a integer in `c(1,2,3,4)` that specifies what mean function is used for data generation of the first sample. Value `1,2,3,4` correspond to quadratic, exponential, cubic and sine functions described in the paper respectively.
`noise.type`	'Func'/'Const' indicating heterogeneous or homogeneous variance for measurement error.
`lam1, lam2`	the eigenvalues used to adjust subject-level variation in simulation data.
`delta`	a parameter indicating the scale of difference between two samples' mean functions.
`iter`	random seed.

This R package is the implementation program for manuscript entitled "Simultaneous Confidence Corridors for Mean Functions in Functional Data Analysis of Imaging Data" by Yueying Wang, Guannan Wang, Li Wang and R. Todd Ogden.

funstatpackages/ImageSCC documentation built on March 3, 2020, 12:25 a.m.