data.SVCMimage: Generating simulation examples

In funstatpackages/SVCMimage: Multivariate Spline Estimation and Inference for Varying Coefficient Models with Imaging Data

Description

This function is used to generate the simulation examples for varying coefficient models with imaging data.

Usage

data.SVCMimage(n, Z, ind.inside, sigma, rho = 0.5, iter = 2019,
  lambda1 = 0.03, lambda2 = 0.006)

Arguments

n	The number of images.
Z	The cooridinates of dimension npix by two. Each row is the coordinates of a pixel/voxel.
ind.inside	The indices of the pixels/voxels which are inside the boundary.
sigma	The level of white noise.
rho	The correlation used to generate the explanatory variales – default is 0.5.
iter	The seed used to generate the simulation examples – default is 2019.
lambda1&lambda2	The eigenvalues used to generate the simulation examples – default are 0.03 and 0.006, respectively.

Details

This R package is the implementation program for manuscript entitled “Multivariate Spline Estimation and Inference for Varying Coefficient Models with Imaging Data" by Shan Yu, Guannan Wang, Li Wang and Lijian Yang.

Value

Y	The response images.
X	The covariates.
Z	The coordinates of the pixels/voxels.
beta.true	The true coefficient functions.

funstatpackages/SVCMimage documentation built on May 17, 2019, 4:21 a.m.