GET (version 1.0-5)

imageset3: A simulated set of images

Description

A simulated set of images with a categorical factor (with three levels)

Usage

data("imageset3")

Format

A list of the image_set containing the simulated images, and the discrete group factor in the list component Group.

Details

We considered a categorical factor Group obtaining the values 0, 1 or 2 according to the group to which the image belongs to (10 images in each of the three groups). The images were simulated in the square window [-1,1]^2 from the general linear model (GLM) $$Y(r) = \exp(-10\cdot ||r||) \cdot (1 + \mathbf{1}(g=2)) + \epsilon(r),$$ where ||r|| denotes the Euclidean distance of the pixel to the origin, g is the group and the error stems from an inhomogeneous distribution over $I$ with the normal and bimodal errors in the middle and periphery of the image: $$\epsilon(r) = \mathbf{1}(\|r\| \leq 0.5) G(r) + \mathbf{1}(\|r\| > 0.5) \frac{1}{2}G(r)^{1/5},$$ where G(r) is a Gaussian random field with the exponential correlation structure with scale parameter 0.15 and standard deviation 0.2. Consequently, the first two groups (0,1) have the same mean, while a bigger bump appears in the third group (2) in the middle of the image.

References

Mrkvička, T., Myllymäki, M., Kuronen, M. and Narisetty, N. N. (2022) New methods for multiple testing in permutation inference for the general linear model. Statistics in Medicine 41(2), 276-297. doi: 10.1002/sim.9236

See Also

graph.fanova, frank.fanova

Examples

data("imageset3")
plot(imageset3$image_set, idx=c(1:5, 11:15, 21:25), ncol=5)
# \donttest{
# Colors can be changed as follows:
plot(imageset3$image_set, idx=c(1:5, 11:15, 21:25), ncol=5) +
  ggplot2::scale_fill_gradient(low="black", high="white")
# }