Generate an order-3 random tensor based on tensor block model.
getOrder3Tensor(
n,
p,
q,
k = NULL,
r = NULL,
l = NULL,
error = 3,
sort = TRUE,
sparse.percent = 0,
center = FALSE,
seed = NULL,
mumin = -3,
mumax = 3
)the dimension at mode 1
the dimension at mode 2
the dimension at mode 3
an positive integer, the numbers of clusters at mode 1
an positive integer, the numbers of clusters at mode 2
an positive integer, the numbers of clusters at mode 3
a positive numeric value, noise level
if TRUE, the tensor entries belonging to the same cluster would be assumed together
the proportion of zero entries based on the Gaussian tensor block model
if True, the data tensor would be centered to zero-mean before clustering
a positive integer, used to specify the random seed
a numeric value, the lower bound of the block mean
a numeric value, the upper bound of the block mean
a list
x the tensor
truthX the underlying signal tensor following block model
truthCs true cluster label assignment at mode 1
truthDs true cluster label assignment at mode 2
truthEs true cluster label assignment at mode 3
mus the block means
binaryX the 0-1 tensor (0:the mean signal = 0; 1:the mean signal != 0)
# NOT RUN {
getOrder3Tensor(20,20,20,2,2,2)$x
# }
Run the code above in your browser using DataLab