imageset3 | R Documentation |
A simulated set of images with a categorical factor (with three levels)
data("imageset3")
A list of the image_set
containing the simulated images, and
the discrete group factor in the list component Group
.
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.
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
graph.fanova
, frank.fanova
data("imageset3")
plot(imageset3$image_set, idx=c(1:5, 11:15, 21:25), ncol=5)
# Colors can be changed as follows:
plot(imageset3$image_set, idx=c(1:5, 11:15, 21:25), ncol=5) +
ggplot2::scale_fill_gradient(low="black", high="white")
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